SecurityScorecard

Embed with customers to build AI-native security solutions integrating SecurityScorecard and manage technical relationships. | 8+ years software engineering with AI, data science, full-stack and cloud architecture experience, plus strong communication skills. | About SecurityScorecard: SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint. Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital. About the Role: SecurityScorecard is hiring a Senior Forward Deployed Engineer to embed with our most strategic customers and turn raw security data into decisions executives act on. You'll deploy onsite, learn the customer's workflow, data, and decision logic firsthand, and build SecurityScorecard directly into how they already operate, closing gaps and creating new value instead of bolting on a generic integration. We're an AI product company at our core, so our FDEs build AI-first: using LLMs and modern AI tooling by default, and applying real data science to help customers quantify risk in terms finance already trusts. What You'll Do Deploy onsite with strategic customers to map their security, risk, and compliance workflows end to end, and find where value is leaking through manual effort or disconnected tools Gather requirements from practitioners and executives, and understand the dependencies across their people, process, and data before proposing a solution Weave SecurityScorecard into the customer's existing data, logic, and process, rather than forcing them to adapt to a generic integration Build AI-native solutions by default: apply LLMs, ML models, and modern AI tooling to automate analysis and cut manual toil Run data analysis and data science work on customer and platform data, for example translating letter-grade ratings into financial terms like Annualized Loss Expectancy (ALE), Value at Risk (VaR), and ROI Design and deploy integrations, pipelines, and tools connecting SecurityScorecard to customer systems (SIEM, GRC, ticketing, data warehouses, and more) Architect and deploy solutions across AWS, Azure, and GCP environments to match each customer's cloud footprint Prototype rapidly in the field, then harden solutions into supportable, production quality software Bridge Product, Engineering, and the customer, feeding field patterns back into the roadmap Own technical relationships with key accounts through renewal and expansion, alongside Customer Success and Sales Engineering Travel to customer sites for workshops, technical deep dives, and go-live support Required Qualifications: 8+ years of software engineering experience, with significant time in a customer-facing, forward deployed, or solutions engineering capacity Hands-on experience building with AI, using LLMs, agentic frameworks, or ML models as core building blocks in shipped solutions A track record building AI-powered products or features, and a clear point of view on how AI changes forward deployed work Working data analysis / data science ability: comfortable turning raw data into a model a customer can act on (risk quantification, benchmarking, exposure modeling) Proven ability to ship production code independently in fast-moving, ambiguous, customer-facing environments Strong full stack fluency: backend services, APIs, scripting, data pipelines, and integration patterns (REST, webhooks, SSO/SAML, SIEM connectors) Solid architecture design experience across AWS, Azure, and GCP, and comfort designing solutions that fit a customer's existing cloud environment Experience running discovery with enterprise stakeholders, from practitioners to executive sponsors, and scoping that into a technical solution Excellent communication skills, translating between technical detail and business or financial impact Bias toward action and comfort with ambiguity Prior experience in cybersecurity, GRC, or risk management is a strong plus Willingness to travel to customer sites (typically 20 to 40%, depending on account load) Benefits: Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more! The estimated total compensation range for this position is $180,000 - $240,000 (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits. SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law. We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io. Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law. SecurityScorecard does not accept unsolicited resumes from employment agencies. Please note that we do not provide immigration sponsorship for this position. #LI-DNI

Embed with customers to build AI-native security solutions integrating SecurityScorecard. | 8+ years software engineering with AI, data science, cloud proficiency, and customer-facing experience. | About SecurityScorecard: SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint. Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital. About the Role: SecurityScorecard is hiring a Senior Forward Deployed Engineer to embed with our most strategic customers and turn raw security data into decisions executives act on. You'll deploy onsite, learn the customer's workflow, data, and decision logic firsthand, and build SecurityScorecard directly into how they already operate, closing gaps and creating new value instead of bolting on a generic integration. We're an AI product company at our core, so our FDEs build AI-first: using LLMs and modern AI tooling by default, and applying real data science to help customers quantify risk in terms finance already trusts. What You'll Do Deploy onsite with strategic customers to map their security, risk, and compliance workflows end to end, and find where value is leaking through manual effort or disconnected tools Gather requirements from practitioners and executives, and understand the dependencies across their people, process, and data before proposing a solution Weave SecurityScorecard into the customer's existing data, logic, and process, rather than forcing them to adapt to a generic integration Build AI-native solutions by default: apply LLMs, ML models, and modern AI tooling to automate analysis and cut manual toil Run data analysis and data science work on customer and platform data, for example translating letter-grade ratings into financial terms like Annualized Loss Expectancy (ALE), Value at Risk (VaR), and ROI Design and deploy integrations, pipelines, and tools connecting SecurityScorecard to customer systems (SIEM, GRC, ticketing, data warehouses, and more) Architect and deploy solutions across AWS, Azure, and GCP environments to match each customer's cloud footprint Prototype rapidly in the field, then harden solutions into supportable, production quality software Bridge Product, Engineering, and the customer, feeding field patterns back into the roadmap Own technical relationships with key accounts through renewal and expansion, alongside Customer Success and Sales Engineering Travel to customer sites for workshops, technical deep dives, and go-live support Required Qualifications: 8+ years of software engineering experience, with significant time in a customer-facing, forward deployed, or solutions engineering capacity Hands-on experience building with AI, using LLMs, agentic frameworks, or ML models as core building blocks in shipped solutions A track record building AI-powered products or features, and a clear point of view on how AI changes forward deployed work Working data analysis / data science ability: comfortable turning raw data into a model a customer can act on (risk quantification, benchmarking, exposure modeling) Proven ability to ship production code independently in fast-moving, ambiguous, customer-facing environments Strong full stack fluency: backend services, APIs, scripting, data pipelines, and integration patterns (REST, webhooks, SSO/SAML, SIEM connectors) Solid architecture design experience across AWS, Azure, and GCP, and comfort designing solutions that fit a customer's existing cloud environment Experience running discovery with enterprise stakeholders, from practitioners to executive sponsors, and scoping that into a technical solution Excellent communication skills, translating between technical detail and business or financial impact Bias toward action and comfort with ambiguity Prior experience in cybersecurity, GRC, or risk management is a strong plus Willingness to travel to customer sites (typically 20 to 40%, depending on account load) Benefits: Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more! Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits. SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law. We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io. Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law. SecurityScorecard does not accept unsolicited resumes from employment agencies. Please note that we do not provide immigration sponsorship for this position. #LI-DNI

Lead engineering delivery of threat intelligence research outputs into production-ready artifacts and platforms. | 5-8 years engineering experience with threat intelligence, production systems, Python, TypeScript, cloud infrastructure, and knowledge of threat intel standards and tooling. | About SecurityScorecard: SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint. Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital. About the Role: You'll join STRIKE, SecurityScorecard's Threat Intelligence team, as the engineering counterpart to research. STRIKE runs several research motions in parallel, each on its own clock: rapid response to active events, longer product-tied work, and standards-anchored research on a quarterly cadence. The path from a finding to a shipped detection or feed gets reinvented every time. That's the problem this role is here to solve. You'll work directly with the senior technical leader who owns STRIKE's R&D direction, and report to the Head of Threat Research for people management. Technical direction comes from R&D leadership; you own delivery. You'll take a research artifact (a malware finding, an infrastructure cluster, a new indicator class, a behavioral pattern) and turn it into something the company can use without a second round of engineering: schemas, pipeline hooks, distribution feeds, detection rules, or platform APIs. This isn't a pure research role, and it isn't a pure platform role either. Researchers ideate, you ship. Key Responsibilities: Research-to-Production Pipeline • Own the path from research output to production-ready artifact: a detection rule, a distributed feed, a scoring input, or a customer alert. Partner with adjacent teams to define clean handoff contracts, so new signals arrive downstream with the schema, value framing, and consumption pattern already defined. Threat Intelligence Platform Engineering • Build and maintain STRIKE platform components across multiple services and runtimes, including distribution servers, sandbox orchestration, OSINT ingestion, federated sharing endpoints, agent runtimes, and rules engines that operate over standards-anchored predicates. Extend these systems without breaking the data contracts already in production. Detection Content and Signal Production • Turn research into shipped detection content: YARA, Sigma, STIX patterns, behavioral indicators, and the pipelines that distribute them. Build correlation pipelines that link scan data, attack surface signals, vulnerability data, and adversary tracking into customer-facing intelligence. Data Model and Standards Adoption • Drive STIX 2.1 adoption as a unified output schema and TAXII 2.1 as a distribution standard. Define and govern schemas that hold up once they reach downstream teams. Research Workflow Engineering • Build the automation that removes commodity overhead from research work: indicator enrichment, report drafting, corpus correlation, feed normalization, and sandbox triage. Help move the team from analyst-driven, model-assisted workflows toward model-driven workflows with analyst review. • The work that matters most here is often the unglamorous part: retrieval grounded in the team's own corpus so outputs cite sources rather than model priors, schema-constrained output so a generated indicator is a valid one, and eval harnesses that catch regressions before analysts do. Cost accounting, latency budgeting, prompt versioning, and output logging round out the infrastructure that makes a workflow safe to run unattended. • You should have a clear sense of when a model is the wrong tool. A regex beats a model for known patterns; a SQL query beats a model for structured data. Knowing where that line sits, and respecting it, is part of the job. Cross-Functional Delivery • Coordinate with engineering, measurement, and platform product teams so research actually lands in product. You'll often serve as the engineering voice translating between researchers, product managers, and platform engineers, and you may occasionally explain the work to customers, journalists, or executives. Qualifications Education: Bachelor's or Master's in Computer Science, Cybersecurity, or a related technical field. Self-taught practitioners with strong public work are welcome. Experience: 5 to 8 years in a hands-on engineering role with meaningful exposure to threat intelligence, security research, or detection engineering. Prior experience building production systems that consume or emit threat intel data is required. Technical Skills: • Python and TypeScript/Node at a production level • Relational and cache data stores, plus at least one streaming or batch data platform • Cloud infrastructure (AWS preferred), containers, and CI/CD pipelines • Working knowledge of STIX 2.1, TAXII 2.1, MISP, and MITRE ATT&CK, and how they work together in practice Detection and Research Tooling: Hands-on experience with YARA, Sigma, and STIX Patterning. Comfortable reading malware analysis output, parsing adversary infrastructure data, and writing detection logic that holds up under production load. Applied Language Models: You've shipped production systems that use language models, not just demos. That includes retrieval over a real corpus, structured output with schema validation, eval harnesses that catch regressions before users do, and a solid understanding of where models fail: recency, long-tail facts, numerical reasoning, and adversarial input or prompt injection. You can do the cost-per-task math for your workloads, and you can make the case when a smaller, tightly scaffolded model beats a larger one. You approach model output with healthy skepticism by default. The bar for shipping a model-generated indicator or detection is higher than for shipping a regex, and you understand why and design accordingly. Bridge Mindset: You write code that ships, and you understand why researchers think the way they do. If you've only ever worked from a backlog handed down by a product manager, this probably isn't the right fit. If you've taken an idea sketched out in a chat message and turned it into a deployed pipeline before the next sprint began, that's the mode we're looking for. Bonus: • Experience with policy-as-code or expression-language engines (CEL, OPA, or similar) • Published or co-authored security research (campaigns, vulnerabilities, adversary tracking) • Large-scale telemetry experience (Splunk, Kinesis, NetFlow, or equivalent) • Contributor or maintainer on open-source threat intel projects (MISP, OpenCTI, Sigma, STIX, ATT&CK) • Familiarity with quantitative risk frameworks such as FAIR • Familiarity with Golang at a production level Benefits: Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more! The estimated total compensation range for this position is $142,500 - $192,500 (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits. SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law. We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io. Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law. SecurityScorecard does not accept unsolicited resumes from employment agencies. Please note that we do not provide immigration sponsorship for this position.

Lead the engineering delivery of threat intelligence research outputs into production-ready artifacts and platform components. | Requires 5-8 years engineering experience with threat intelligence, proficiency in Python and TypeScript, knowledge of threat intel standards, and experience shipping production detection systems. | About SecurityScorecard: SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint. Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital. About the Role: You'll join STRIKE, SecurityScorecard's Threat Intelligence team, as the engineering counterpart to research. STRIKE runs several research motions in parallel, each on its own clock: rapid response to active events, longer product-tied work, and standards-anchored research on a quarterly cadence. The path from a finding to a shipped detection or feed gets reinvented every time. That's the problem this role is here to solve. You'll work directly with the senior technical leader who owns STRIKE's R&D direction, and report to the Head of Threat Research for people management. Technical direction comes from R&D leadership; you own delivery. You'll take a research artifact (a malware finding, an infrastructure cluster, a new indicator class, a behavioral pattern) and turn it into something the company can use without a second round of engineering: schemas, pipeline hooks, distribution feeds, detection rules, or platform APIs. This isn't a pure research role, and it isn't a pure platform role either. Researchers ideate, you ship. Key Responsibilities: Research-to-Production Pipeline • Own the path from research output to production-ready artifact: a detection rule, a distributed feed, a scoring input, or a customer alert. Partner with adjacent teams to define clean handoff contracts, so new signals arrive downstream with the schema, value framing, and consumption pattern already defined. Threat Intelligence Platform Engineering • Build and maintain STRIKE platform components across multiple services and runtimes, including distribution servers, sandbox orchestration, OSINT ingestion, federated sharing endpoints, agent runtimes, and rules engines that operate over standards-anchored predicates. Extend these systems without breaking the data contracts already in production. Detection Content and Signal Production • Turn research into shipped detection content: YARA, Sigma, STIX patterns, behavioral indicators, and the pipelines that distribute them. Build correlation pipelines that link scan data, attack surface signals, vulnerability data, and adversary tracking into customer-facing intelligence. Data Model and Standards Adoption • Drive STIX 2.1 adoption as a unified output schema and TAXII 2.1 as a distribution standard. Define and govern schemas that hold up once they reach downstream teams. Research Workflow Engineering • Build the automation that removes commodity overhead from research work: indicator enrichment, report drafting, corpus correlation, feed normalization, and sandbox triage. Help move the team from analyst-driven, model-assisted workflows toward model-driven workflows with analyst review. • The work that matters most here is often the unglamorous part: retrieval grounded in the team's own corpus so outputs cite sources rather than model priors, schema-constrained output so a generated indicator is a valid one, and eval harnesses that catch regressions before analysts do. Cost accounting, latency budgeting, prompt versioning, and output logging round out the infrastructure that makes a workflow safe to run unattended. • You should have a clear sense of when a model is the wrong tool. A regex beats a model for known patterns; a SQL query beats a model for structured data. Knowing where that line sits, and respecting it, is part of the job. Cross-Functional Delivery • Coordinate with engineering, measurement, and platform product teams so research actually lands in product. You'll often serve as the engineering voice translating between researchers, product managers, and platform engineers, and you may occasionally explain the work to customers, journalists, or executives. Qualifications Education: Bachelor's or Master's in Computer Science, Cybersecurity, or a related technical field. Self-taught practitioners with strong public work are welcome. Experience: 5 to 8 years in a hands-on engineering role with meaningful exposure to threat intelligence, security research, or detection engineering. Prior experience building production systems that consume or emit threat intel data is required. Technical Skills: • Python and TypeScript/Node at a production level • Relational and cache data stores, plus at least one streaming or batch data platform • Cloud infrastructure (AWS preferred), containers, and CI/CD pipelines • Working knowledge of STIX 2.1, TAXII 2.1, MISP, and MITRE ATT&CK, and how they work together in practice Detection and Research Tooling: Hands-on experience with YARA, Sigma, and STIX Patterning. Comfortable reading malware analysis output, parsing adversary infrastructure data, and writing detection logic that holds up under production load. Applied Language Models: You've shipped production systems that use language models, not just demos. That includes retrieval over a real corpus, structured output with schema validation, eval harnesses that catch regressions before users do, and a solid understanding of where models fail: recency, long-tail facts, numerical reasoning, and adversarial input or prompt injection. You can do the cost-per-task math for your workloads, and you can make the case when a smaller, tightly scaffolded model beats a larger one. You approach model output with healthy skepticism by default. The bar for shipping a model-generated indicator or detection is higher than for shipping a regex, and you understand why and design accordingly. Bridge Mindset: You write code that ships, and you understand why researchers think the way they do. If you've only ever worked from a backlog handed down by a product manager, this probably isn't the right fit. If you've taken an idea sketched out in a chat message and turned it into a deployed pipeline before the next sprint began, that's the mode we're looking for. Bonus: • Experience with policy-as-code or expression-language engines (CEL, OPA, or similar) • Published or co-authored security research (campaigns, vulnerabilities, adversary tracking) • Large-scale telemetry experience (Splunk, Kinesis, NetFlow, or equivalent) • Contributor or maintainer on open-source threat intel projects (MISP, OpenCTI, Sigma, STIX, ATT&CK) • Familiarity with quantitative risk frameworks such as FAIR • Familiarity with Golang at a production level Benefits: Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more! The estimated total compensation range for this position is $142,500 - $192,500 (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits. SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law. We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io. Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law. SecurityScorecard does not accept unsolicited resumes from employment agencies. Please note that we do not provide immigration sponsorship for this position.

Track and analyze threat actors, produce intelligence reports, and communicate findings to various stakeholders. | 3-5 years hands-on threat intelligence research experience, proficiency in data querying tools, and strong communication skills. | About SecurityScorecard: SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint. Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital. About the Role: You'll be joining SecurityScorecard's threat research team as its intelligence-focused practitioner, working alongside deep technical researchers to produce timely, actionable intelligence for customers, partners, and internal stakeholders. Where the Threat Researcher role is anchored in technical analysis, this role sits at the intersection of research and communication — you'll be tracking threat actors and their infrastructure, producing intelligence reports, and translating complex findings into clear, credible content for a range of audiences. Marketing is currently one of the team's primary stakeholders, and you'll work closely with them on research-driven content and campaigns — but the team's ambition is to become a resource for every division in the company, and you'll be part of building that reputation. Customer briefings, coordinated threat actor takedowns, and participation in industry events are all part of the mandate. Strong written and spoken English is essential, as is the ability to represent the team's work credibly in external settings. This is a role for someone who combines analytical depth with the communication skills to make that work land. Key Responsibilities: • Deep Technical Research and Tracking: Identify, track, and analyze advanced persistent threats (APTs), their TTPs, and their live infrastructure to gain insights into attack vectors, victimology, and attack scale. • Intelligence Briefing and Reporting: Produce timely and actionable intelligence reports for customers, press, and partners. Participate in customer briefings, incident mitigation, and coordinated threat actor (TA) takedowns. • Detection Engineering: Develop and maintain high-fidelity detection signatures (YARA, Snort, Sigma) to protect customers. • Hunting and Monitoring: Query massive datasets (using SQL, Python, or Splunk) to identify anomalies and map out adversary infrastructure. Build workbooks, dashboards, and develop methodologies to improve detections. • AI and LLM Automation: Design and leverage AI and LLM automations to support your analysis workload. Qualifications: • Education: Bachelor's or Master's in Computer Science, Cybersecurity, or a highly technical equivalent. • Experience: 3–5 years in a hands-on threat intelligence research role within a prominent industry organization, military, law enforcement, or government. • Knowledge: Familiarity with prominent threat actors, APTs, emerging threat vectors, and the wider threat landscape. • Technical Skills: Proficiency with large dataset querying and dashboard design using Splunk, SQL, or similar platforms. • Mindset: A hacker's curiosity — the ability to look at a data point and see the hidden pattern. • Bonus: Experience with open source and commercial attack surface, malware analysis, and network intelligence tools and platforms. • Additional Bonus: Native-level reading and writing proficiency in Russian, Mandarin, Korean, or Farsi. Benefits: Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more! The estimated total compensation range for this position is $100,000 - $120,000 (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits. SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law. We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io. Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law. SecurityScorecard does not accept unsolicited resumes from employment agencies. Please note that we do not provide immigration sponsorship for this position.

Translate threat research findings into production-ready detection content and platform components. | Requires 5-8 years engineering experience with threat intelligence, production coding in Python/TypeScript, and knowledge of STIX/TAXII standards. | About the Role: You'll join STRIKE, SecurityScorecard's Threat Intelligence team, as the engineering counterpart to research. STRIKE runs several research motions in parallel, each on its own clock: rapid response to active events, longer product-tied work, and standards-anchored research on a quarterly cadence. The path from a finding to a shipped detection or feed gets reinvented every time. That's the problem this role is here to solve. You'll work directly with the senior technical leader who owns STRIKE's R&D direction, and report to the Head of Threat Research for people management. Technical direction comes from R&D leadership; you own delivery. You'll take a research artifact (a malware finding, an infrastructure cluster, a new indicator class, a behavioral pattern) and turn it into something the company can use without a second round of engineering: schemas, pipeline hooks, distribution feeds, detection rules, or platform APIs. This isn't a pure research role, and it isn't a pure platform role either. Researchers ideate, you ship. Key Responsibilities: Research-to-Production Pipeline • Own the path from research output to production-ready artifact: a detection rule, a distributed feed, a scoring input, or a customer alert. Partner with adjacent teams to define clean handoff contracts, so new signals arrive downstream with the schema, value framing, and consumption pattern already defined. Threat Intelligence Platform Engineering • Build and maintain STRIKE platform components across multiple services and runtimes, including distribution servers, sandbox orchestration, OSINT ingestion, federated sharing endpoints, agent runtimes, and rules engines that operate over standards-anchored predicates. Extend these systems without breaking the data contracts already in production. Detection Content and Signal Production • Turn research into shipped detection content: YARA, Sigma, STIX patterns, behavioral indicators, and the pipelines that distribute them. Build correlation pipelines that link scan data, attack surface signals, vulnerability data, and adversary tracking into customer-facing intelligence. Data Model and Standards Adoption • Drive STIX 2.1 adoption as a unified output schema and TAXII 2.1 as a distribution standard. Define and govern schemas that hold up once they reach downstream teams. Research Workflow Engineering • Build the automation that removes commodity overhead from research work: indicator enrichment, report drafting, corpus correlation, feed normalization, and sandbox triage. Help move the team from analyst-driven, model-assisted workflows toward model-driven workflows with analyst review. • The work that matters most here is often the unglamorous part: retrieval grounded in the team's own corpus so outputs cite sources rather than model priors, schema-constrained output so a generated indicator is a valid one, and eval harnesses that catch regressions before analysts do. Cost accounting, latency budgeting, prompt versioning, and output logging round out the infrastructure that makes a workflow safe to run unattended. • You should have a clear sense of when a model is the wrong tool. A regex beats a model for known patterns; a SQL query beats a model for structured data. Knowing where that line sits, and respecting it, is part of the job. Cross-Functional Delivery • Coordinate with engineering, measurement, and platform product teams so research actually lands in product. You'll often serve as the engineering voice translating between researchers, product managers, and platform engineers, and you may occasionally explain the work to customers, journalists, or executives. Qualifications Education: Bachelor's or Master's in Computer Science, Cybersecurity, or a related technical field. Self-taught practitioners with strong public work are welcome. Experience: 5 to 8 years in a hands-on engineering role with meaningful exposure to threat intelligence, security research, or detection engineering. Prior experience building production systems that consume or emit threat intel data is required. Technical Skills: • Python and TypeScript/Node at a production level • Relational and cache data stores, plus at least one streaming or batch data platform • Cloud infrastructure (AWS preferred), containers, and CI/CD pipelines • Working knowledge of STIX 2.1, TAXII 2.1, MISP, and MITRE ATT&CK, and how they work together in practice Detection and Research Tooling: Hands-on experience with YARA, Sigma, and STIX Patterning. Comfortable reading malware analysis output, parsing adversary infrastructure data, and writing detection logic that holds up under production load. Applied Language Models: You've shipped production systems that use language models, not just demos. That includes retrieval over a real corpus, structured output with schema validation, eval harnesses that catch regressions before users do, and a solid understanding of where models fail: recency, long-tail facts, numerical reasoning, and adversarial input or prompt injection. You can do the cost-per-task math for your workloads, and you can make the case when a smaller, tightly scaffolded model beats a larger one. You approach model output with healthy skepticism by default. The bar for shipping a model-generated indicator or detection is higher than for shipping a regex, and you understand why and design accordingly. Bridge Mindset: You write code that ships, and you understand why researchers think the way they do. If you've only ever worked from a backlog handed down by a product manager, this probably isn't the right fit. If you've taken an idea sketched out in a chat message and turned it into a deployed pipeline before the next sprint began, that's the mode we're looking for. Bonus: • Experience with policy-as-code or expression-language engines (CEL, OPA, or similar) • Published or co-authored security research (campaigns, vulnerabilities, adversary tracking) • Large-scale telemetry experience (Splunk, Kinesis, NetFlow, or equivalent) • Contributor or maintainer on open-source threat intel projects (MISP, OpenCTI, Sigma, STIX, ATT&CK) • Familiarity with quantitative risk frameworks such as FAIR • Familiarity with Golang at a production level Benefits: Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more! The estimated total compensation range for this position is $140,00 - $150,000 (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits.

Convert threat research into scalable detection systems and automate workflows using LLMs and data pipelines. | 5-8 years in threat intelligence or security research with Python and TypeScript proficiency and experience shipping production LLM systems. | About SecurityScorecard: SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint. Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital. About the Role: You'll join STRIKE, SecurityScorecard's Threat Intelligence team, as the engineering counterpart to research. STRIKE runs several research motions in parallel, each on its own clock: rapid response to active events, longer product-tied work, and standards-anchored research on a quarterly cadence. The path from a finding to a shipped detection or feed gets reinvented every time. That's the problem this role is here to solve. You'll work directly with the senior technical leader who owns STRIKE's R&D direction, and report to the Head of Threat Research for people management. Technical direction comes from R&D leadership; you own delivery. You'll take a research artifact (a malware finding, an infrastructure cluster, a new indicator class, a behavioral pattern) and turn it into something the company can use without a second round of engineering: schemas, pipeline hooks, distribution feeds, detection rules, or platform APIs. This isn't a pure research role, and it isn't a pure platform role either. Researchers ideate, you ship. Key Responsibilities: Research-to-Production Pipeline Own the path from research output to production-ready artifact: a detection rule, a distributed feed, a scoring input, or a customer alert. Partner with adjacent teams to define clean handoff contracts, so new signals arrive downstream with the schema, value framing, and consumption pattern already defined. Threat Intelligence Platform Engineering Build and maintain STRIKE platform components across multiple services and runtimes, including distribution servers, sandbox orchestration, OSINT ingestion, federated sharing endpoints, agent runtimes, and rules engines that operate over standards-anchored predicates. Extend these systems without breaking the data contracts already in production. Detection Content and Signal Production Turn research into shipped detection content: YARA, Sigma, STIX patterns, behavioral indicators, and the pipelines that distribute them. Build correlation pipelines that link scan data, attack surface signals, vulnerability data, and adversary tracking into customer-facing intelligence. Data Model and Standards Adoption Drive STIX 2.1 adoption as a unified output schema and TAXII 2.1 as a distribution standard. Define and govern schemas that hold up once they reach downstream teams. Research Workflow Engineering Build the automation that removes commodity overhead from research work: indicator enrichment, report drafting, corpus correlation, feed normalization, and sandbox triage. Help move the team from analyst-driven, model-assisted workflows toward model-driven workflows with analyst review. The work that matters most here is often the unglamorous part: retrieval grounded in the team's own corpus so outputs cite sources rather than model priors, schema-constrained output so a generated indicator is a valid one, and eval harnesses that catch regressions before analysts do. Cost accounting, latency budgeting, prompt versioning, and output logging round out the infrastructure that makes a workflow safe to run unattended. You should have a clear sense of when a model is the wrong tool. A regex beats a model for known patterns; a SQL query beats a model for structured data. Knowing where that line sits, and respecting it, is part of the job. Cross-Functional Delivery Coordinate with engineering, measurement, and platform product teams so research actually lands in product. You'll often serve as the engineering voice translating between researchers, product managers, and platform engineers, and you may occasionally explain the work to customers, journalists, or executives. Qualifications Education: Bachelor's or Master's in Computer Science, Cybersecurity, or a related technical field. Self-taught practitioners with strong public work are welcome. Experience: 5 to 8 years in a hands-on engineering role with meaningful exposure to threat intelligence, security research, or detection engineering. Prior experience building production systems that consume or emit threat intel data is required. Technical Skills: Python and TypeScript/Node at a production level Relational and cache data stores, plus at least one streaming or batch data platform Cloud infrastructure (AWS preferred), containers, and CI/CD pipelines Working knowledge of STIX 2.1, TAXII 2.1, MISP, and MITRE ATT&CK, and how they work together in practice Detection and Research Tooling: Hands-on experience with YARA, Sigma, and STIX Patterning. Comfortable reading malware analysis output, parsing adversary infrastructure data, and writing detection logic that holds up under production load. Applied Language Models: You've shipped production systems that use language models, not just demos. That includes retrieval over a real corpus, structured output with schema validation, eval harnesses that catch regressions before users do, and a solid understanding of where models fail: recency, long-tail facts, numerical reasoning, and adversarial input or prompt injection. You can do the cost-per-task math for your workloads, and you can make the case when a smaller, tightly scaffolded model beats a larger one. You approach model output with healthy skepticism by default. The bar for shipping a model-generated indicator or detection is higher than for shipping a regex, and you understand why and design accordingly. Bridge Mindset: You write code that ships, and you understand why researchers think the way they do. If you've only ever worked from a backlog handed down by a product manager, this probably isn't the right fit. If you've taken an idea sketched out in a chat message and turned it into a deployed pipeline before the next sprint began, that's the mode we're looking for. Bonus: Experience with policy-as-code or expression-language engines (CEL, OPA, or similar) Published or co-authored security research (campaigns, vulnerabilities, adversary tracking) Large-scale telemetry experience (Splunk, Kinesis, NetFlow, or equivalent) Contributor or maintainer on open-source threat intel projects (MISP, OpenCTI, Sigma, STIX, ATT&CK) Familiarity with quantitative risk frameworks such as FAIR Familiarity with Golang at a production level Benefits: Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more! The estimated total compensation range for this position is $140,00 - $150,000 (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits. SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law. We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io. Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law. SecurityScorecard does not accept unsolicited resumes from employment agencies. Please note that we do not provide immigration sponsorship for this position. #LI-DNI

Translate threat research into production-ready detection content and platform components, coordinating cross-functional delivery. | 5-8 years engineering experience in threat intelligence or detection engineering with strong Python/TypeScript skills, cloud infrastructure knowledge, and familiarity with STIX, TAXII, and MITRE ATT&CK. | About SecurityScorecard: SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint. Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital. About the Role: You'll join STRIKE, SecurityScorecard's Threat Intelligence team, as the engineering counterpart to research. STRIKE runs several research motions in parallel, each on its own clock: rapid response to active events, longer product-tied work, and standards-anchored research on a quarterly cadence. The path from a finding to a shipped detection or feed gets reinvented every time. That's the problem this role is here to solve. You'll work directly with the senior technical leader who owns STRIKE's R&D direction, and report to the Head of Threat Research for people management. Technical direction comes from R&D leadership; you own delivery. You'll take a research artifact (a malware finding, an infrastructure cluster, a new indicator class, a behavioral pattern) and turn it into something the company can use without a second round of engineering: schemas, pipeline hooks, distribution feeds, detection rules, or platform APIs. This isn't a pure research role, and it isn't a pure platform role either. Researchers ideate, you ship. Key Responsibilities: Research-to-Production Pipeline • Own the path from research output to production-ready artifact: a detection rule, a distributed feed, a scoring input, or a customer alert. Partner with adjacent teams to define clean handoff contracts, so new signals arrive downstream with the schema, value framing, and consumption pattern already defined. Threat Intelligence Platform Engineering • Build and maintain STRIKE platform components across multiple services and runtimes, including distribution servers, sandbox orchestration, OSINT ingestion, federated sharing endpoints, agent runtimes, and rules engines that operate over standards-anchored predicates. Extend these systems without breaking the data contracts already in production. Detection Content and Signal Production • Turn research into shipped detection content: YARA, Sigma, STIX patterns, behavioral indicators, and the pipelines that distribute them. Build correlation pipelines that link scan data, attack surface signals, vulnerability data, and adversary tracking into customer-facing intelligence. Data Model and Standards Adoption • Drive STIX 2.1 adoption as a unified output schema and TAXII 2.1 as a distribution standard. Define and govern schemas that hold up once they reach downstream teams. Research Workflow Engineering • Build the automation that removes commodity overhead from research work: indicator enrichment, report drafting, corpus correlation, feed normalization, and sandbox triage. Help move the team from analyst-driven, model-assisted workflows toward model-driven workflows with analyst review. • The work that matters most here is often the unglamorous part: retrieval grounded in the team's own corpus so outputs cite sources rather than model priors, schema-constrained output so a generated indicator is a valid one, and eval harnesses that catch regressions before analysts do. Cost accounting, latency budgeting, prompt versioning, and output logging round out the infrastructure that makes a workflow safe to run unattended. • You should have a clear sense of when a model is the wrong tool. A regex beats a model for known patterns; a SQL query beats a model for structured data. Knowing where that line sits, and respecting it, is part of the job. Cross-Functional Delivery • Coordinate with engineering, measurement, and platform product teams so research actually lands in product. You'll often serve as the engineering voice translating between researchers, product managers, and platform engineers, and you may occasionally explain the work to customers, journalists, or executives. Qualifications Education: Bachelor's or Master's in Computer Science, Cybersecurity, or a related technical field. Self-taught practitioners with strong public work are welcome. Experience: 5 to 8 years in a hands-on engineering role with meaningful exposure to threat intelligence, security research, or detection engineering. Prior experience building production systems that consume or emit threat intel data is required. Technical Skills: • Python and TypeScript/Node at a production level • Relational and cache data stores, plus at least one streaming or batch data platform • Cloud infrastructure (AWS preferred), containers, and CI/CD pipelines • Working knowledge of STIX 2.1, TAXII 2.1, MISP, and MITRE ATT&CK, and how they work together in practice Detection and Research Tooling: Hands-on experience with YARA, Sigma, and STIX Patterning. Comfortable reading malware analysis output, parsing adversary infrastructure data, and writing detection logic that holds up under production load. Applied Language Models: You've shipped production systems that use language models, not just demos. That includes retrieval over a real corpus, structured output with schema validation, eval harnesses that catch regressions before users do, and a solid understanding of where models fail: recency, long-tail facts, numerical reasoning, and adversarial input or prompt injection. You can do the cost-per-task math for your workloads, and you can make the case when a smaller, tightly scaffolded model beats a larger one. You approach model output with healthy skepticism by default. The bar for shipping a model-generated indicator or detection is higher than for shipping a regex, and you understand why and design accordingly. Bridge Mindset: You write code that ships, and you understand why researchers think the way they do. If you've only ever worked from a backlog handed down by a product manager, this probably isn't the right fit. If you've taken an idea sketched out in a chat message and turned it into a deployed pipeline before the next sprint began, that's the mode we're looking for. Bonus: • Experience with policy-as-code or expression-language engines (CEL, OPA, or similar) • Published or co-authored security research (campaigns, vulnerabilities, adversary tracking) • Large-scale telemetry experience (Splunk, Kinesis, NetFlow, or equivalent) • Contributor or maintainer on open-source threat intel projects (MISP, OpenCTI, Sigma, STIX, ATT&CK) • Familiarity with quantitative risk frameworks such as FAIR • Familiarity with Golang at a production level Benefits: Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more! The estimated total compensation range for this position is $142,500 - $192,500 (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits. SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law. We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io. Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law. SecurityScorecard does not accept unsolicited resumes from employment agencies. Please note that we do not provide immigration sponsorship for this position.