DataVisor

Design and maintain high-throughput data pipelines, develop AI applications leveraging large language models, and optimize distributed systems for real-time fraud detection. | 1-5 years experience in ML/Data Engineering, proficiency in distributed data frameworks, programming skills in Python and a compiled language, experience with cloud-native systems. | DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe. Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us! Role Summary We are hiring an AI/ML Engineer to serve as a technical architect for our Intelligence Layer and Data Consortium. This is a specialized engineering role—distinct from general web development—focused on building the high-scale "muscle" that powers our fraud intelligence. You will design and maintain distributed pipelines that ingest real-time signals from millions of users, and engineer backend systems that enable our Agentic Flow to "auto-tune" strategies. You will also play a key role in building agentic flows and AI applications using state-of-the-art, out-of-the-box large language models (LLMs) available on the market, in addition to helping build and deploy traditional machine learning models. Primary Responsibilities Consortium Data Engineering: Architect and maintain high-throughput data pipelines (using Spark, Kafka, or Flink) to ingest, process, and aggregate real-time signals—such as device fingerprints and behavioral biometrics—into our central intelligence graph. High-Scale System Design: Optimize distributed systems to support our global data network, ensuring the platform can handle 10,000+ Transactions Per Second (TPS) with P99 latency under 150ms. Agentic Flow & AI Application Development: Build agentic flows and AI applications by leveraging state-of-the-art, out-of-the-box LLMs (e.g., OpenAI, Anthropic, Google) to enable natural language interaction, intelligent rule merging, and automated fraud strategy recommendations. Productionize ML Pipelines: Deploy and maintain pipelines for both Unsupervised (UML) and Supervised (SML) models, integrating them with our API to enable real-time scoring and decisioning. Privacy-First Architecture: Implement robust security measures, including tokenization and hashing, to ensure PII privacy and compliance across our shared intelligence network. Cross-Functional Collaboration: Work closely with Data Science, Product, Strategy, Delivery, and Engineering teams to develop, validate, and optimize machine learning models and AI-driven features. Qualifications Experience: 1–5 years of experience in Machine Learning Engineering, Data Engineering, or Backend Engineering. System Architecture: Proven ability to design distributed, cloud-native systems for high-throughput applications. Experience with AWS and containerization (Docker/Kubernetes) is critical. Big Data Tech: Strong hands-on experience with distributed data frameworks such as Spark, Kafka, or Flink. Coding Proficiency: Production-grade skills in Python and at least one compiled language (e.g., Java or C++). Preferred Qualifications Experience building or integrating LLM applications (LangChain, Vector DBs, RAG architectures). Background in real-time decision engines or stateful stream processing. Knowledge of fraud or risk domains is a plus, but not required. Base Salary Range: 130K - 200K Total Compensation: Includes Base + Performance Bonus + Equity Options. Benefits: Comprehensive medical, dental, and vision coverage. 401(k) retirement plan. Flexible Time Off (FTO) and paid holidays. Opportunities for R&D exploration and professional development. Regular team-building events and a collaborative, innovative culture.

Develop and optimize fraud detection models, analyze large-scale data, and collaborate across teams to implement machine learning solutions. | 1-5 years of experience in Data Science or Advanced Analytics, proficiency in Python and SQL, solid statistical foundation, and domain knowledge in fraud detection. | About DataVisor: DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe. Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us! Role Summary We are seeking a hands-on Senior Data Scientist to serve as the "Architect of Efficacy" for our AI-Powered Fraud Solutions suite. In this role, you will move beyond simple analysis to build the mathematical core of our product. You will design pre-built detection strategies that provide immediate protection for new clients, solving the industry-wide "Cold Start" problem. Working at the intersection of research and product, you will collaborate closely with our Product, Strategy, Data Science, Delivery, and Engineering teams to translate complex fraud patterns into scalable, automated defenses. Responsibilities Develop Pre-Built Detection Models: Design, back-test, and optimize statistical baselines and machine learning strategies for our core solution modules, including Real-Time Payments (RTP), ACH, Wire, Check, and Application/Onboarding. Mine the Global Consortium: Analyze large-scale, cross-industry data within our global intelligence network to identify high-risk device fingerprints and patterns of organized fraud, transforming these insights into features that can be deployed across all clients. Architect "Cold Start" Logic: Create generalized scoring models that deliver immediate value to new clients, ensuring they are protected against known threats even before their historical data is fully integrated. Validate AI Agent Logic: Serve as the expert "Human-in-the-Loop" for our AI-driven strategy engine, rigorously testing and validating automated fraud detection logic to ensure safety, transparency, and low false positive rates. Cross-Functional R&D: Collaborate with Product, Strategy, Data Science, Delivery, and Engineering teams to explore and implement state-of-the-art machine learning and large language model (LLM) capabilities, providing the statistical rigor needed to turn experimental concepts into production-grade features. Qualifications Experience: 1–5 years of hands-on experience in Data Science or Advanced Analytics. Technical Core: Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL. Statistical Rigor: Solid foundation in statistical modeling, feature selection, and performance evaluation (Precision/Recall, AUC, KS). Preferred Qualifications Experience with graph theory or link analysis for detecting network-based fraud. Familiarity with unsupervised learning techniques or anomaly detection. Previous experience working in a high-growth SaaS or Fintech environment. Domain Knowledge: Familiarity with Fraud Detection, Credit Risk, or Trust & Safety, including knowledge of payment rails (FedNow, ACH, Wire) and typologies (Synthetic ID, ATO, Kiting). Total Compensation: Includes Base + Performance Bonus + Equity Options. Benefits: Comprehensive medical, dental, and vision coverage. 401(k) retirement plan. Flexible Time Off (FTO) and paid holidays. Opportunities for R&D exploration and professional development. Regular team-building events and a collaborative, innovative culture.

Provide product support and escalation, architect fraud solutions, lead pre-sales discussions, manage integrations, conduct business reviews, and drive product roadmap. | 10+ years in customer-facing technical roles in banking, payment, social, or e-commerce industries, strong communication and project management skills, and a technical or analytical degree. | About the position Responsibilities • Provide product support, escalation, and resolution of technical issues • Architect machine learning and rule-based solutions for customers' fraud problems • Lead solution deployment deep dive discussions in late stage pre-sales calls • Understand client use cases and define plans to achieve success criteria • Manage integration and product implementation process for customers • Conduct and coordinate business reviews and presentations with clients • Drive product roadmap by communicating client feedback to internal teams • Attend meetups, events, and conferences as a technical ambassador Requirements • 10+ years of experience in banking, payment, social, or e-commerce industries, as customer facing technical roles e.g. technical account manager or solution consultant • B.A./B.S. degree in a technical or analytical discipline • Excellent communication and presentation skills • Strong time and project management ability with focus to ensure deadlines are met Nice-to-haves • Experience in fraud detection and risk management is a big plus • Coding and database experience (e.g. Python, Java, SQL) a plus Benefits • Bonus • PTO • Stock Option • Health Benefits

Lead the Platform Engineering team to design and build a large-scale AI-based fraud and risk decision platform. Manage a team of engineers while contributing to the development of infrastructure that enables real-time fraud detection. | Candidates should have a BS degree in Computer Science or a related field, with a preference for MS/PhD. A minimum of 8 years of software development experience and 3 years of team management experience is required, along with a solid understanding of AI/ML concepts. | DataVisor is a next-generation SaaS company that protects the world’s largest enterprises from fraud and money laundering. Our award-winning AI decision platform combines industry-leading unsupervised machine learning (UML) with advanced supervised models to stop fraudulent activity across financial transactions, mobile growth, social networks, and e-commerce. We partner with leading global brands, delivering solutions built on top of our highly scalable platform. Behind these innovations is a world-class team of experts in big data, security, and distributed infrastructure, thriving in a culture that is open, collaborative, and results-driven. Join us and help push the boundaries of what’s possible in fraud detection. Role Summary We are seeking a Software Engineering Manager to lead our Platform Engineering team. This team is at the heart of DataVisor’s detection capabilities, building the AI-based fraud and risk decision platform that powers real-time and batch unified decisioning at enterprise scale. You will manage a talented team of engineers while also contributing to the design and development of our next-generation AI agent driven infrastructure. Together, you’ll enable our customers to detect and stop complex fraud patterns in real time. What You’ll Do Design & Build: Architect and deliver a large-scale, AI-based fraud and risk decision platform. Innovate in Fraud Detection: Apply unsupervised, supervised, and agentic AI methods to uncover and stop fraudulent behavior. Unify Decisioning: Drive the development of a real-time and batch unified decision platform that powers enterprise-scale fraud prevention. Scale Infrastructure: Build and optimize distributed, real-time data systems for low-latency decisioning. Leverage Big Data: Utilize Spark, Flink, Cassandra, and related technologies to enable high-throughput ML pipelines. Lead & Mentor: Manage, coach, and grow a team of engineers, fostering technical excellence and professional development. BS degree in Computer Science or related field required; MS/PhD preferred Fluent in Java or C++ programming, with knowledge of Python; hands-on in coding, system design, and architecture 3+ years of experience leading or managing teams 8+ years of software development experience Solid understanding of AI/ML concepts (unsupervised, supervised, and emerging approaches such as agentic AI); experience applying ML in production systems is a strong plus Familiarity with relational databases, SQL, and ORM frameworks (JPA, Hibernate) is a plus Experience with big data technologies (Cassandra, Flink, Spark, Kafka) preferred Knowledge of the Spring Framework is a plus Exposure to test-driven development and high-quality engineering practices Excellent oral and written communication skills Strong team spirit and collaboration mindset Why Join Us Impact at Scale: Work on fraud detection systems processing billions of events daily. Cutting-Edge Tech: Push the frontier in streaming, agentic AI, and big data infrastructure. Career Growth: Lead a high-impact team with opportunities to shape technical direction and grow into senior leadership.

Lead and manage a platform engineering team to design and build a large-scale AI-based fraud detection platform with real-time and batch decisioning capabilities. | 8+ years software development, 3+ years managing teams, fluent in Java or C++, knowledge of Python, BS degree required, AI/ML experience, and familiarity with big data technologies. | DataVisor is a next-generation SaaS company that protects the world’s largest enterprises from fraud and money laundering. Our award-winning AI decision platform combines industry-leading unsupervised machine learning (UML) with advanced supervised models to stop fraudulent activity across financial transactions, mobile growth, social networks, and e-commerce. We partner with leading global brands, delivering solutions built on top of our highly scalable platform. Behind these innovations is a world-class team of experts in big data, security, and distributed infrastructure, thriving in a culture that is open, collaborative, and results-driven. Join us and help push the boundaries of what’s possible in fraud detection. Role Summary We are seeking a Software Engineering Manager to lead our Platform Engineering team. This team is at the heart of DataVisor’s detection capabilities, building the AI-based fraud and risk decision platform that powers real-time and batch unified decisioning at enterprise scale. You will manage a talented team of engineers while also contributing to the design and development of our next-generation AI agent driven infrastructure. Together, you’ll enable our customers to detect and stop complex fraud patterns in real time. What You’ll Do • Design & Build: Architect and deliver a large-scale, AI-based fraud and risk decision platform. • Innovate in Fraud Detection: Apply unsupervised, supervised, and agentic AI methods to uncover and stop fraudulent behavior. • Unify Decisioning: Drive the development of a real-time and batch unified decision platform that powers enterprise-scale fraud prevention. • Scale Infrastructure: Build and optimize distributed, real-time data systems for low-latency decisioning. • Leverage Big Data: Utilize Spark, Flink, Cassandra, and related technologies to enable high-throughput ML pipelines. • Lead & Mentor: Manage, coach, and grow a team of engineers, fostering technical excellence and professional development. • BS degree in Computer Science or related field required; MS/PhD preferred • Fluent in Java or C++ programming, with knowledge of Python; hands-on in coding, system design, and architecture • 3+ years of experience leading or managing teams • 8+ years of software development experience • Solid understanding of AI/ML concepts (unsupervised, supervised, and emerging approaches such as agentic AI); experience applying ML in production systems is a strong plus • Familiarity with relational databases, SQL, and ORM frameworks (JPA, Hibernate) is a plus • Experience with big data technologies (Cassandra, Flink, Spark, Kafka) preferred • Knowledge of the Spring Framework is a plus • Exposure to test-driven development and high-quality engineering practices • Excellent oral and written communication skills • Strong team spirit and collaboration mindset Why Join Us • Impact at Scale: Work on fraud detection systems processing billions of events daily. • Cutting-Edge Tech: Push the frontier in streaming, agentic AI, and big data infrastructure. • Career Growth: Lead a high-impact team with opportunities to shape technical direction and grow into senior leadership.

Design, test, implement, and optimize rules for fraud and AML detection across various activities. Collaborate with teams to translate fraud patterns into actionable strategies and manage workflows for effective monitoring. | Candidates should have over 5 years of experience in fraud or AML strategy within financial services. A strong understanding of payment fraud schemes and proficiency in SQL and analytics tools is required. | DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe. Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us! Position Overview: If you thrive on curiosity, creativity, and staying a step ahead of fraudsters, this role is for you. You’ll bring together a deep understanding of fraud and AML patterns to craft new rules, the curiosity to test emerging data signals, and the discipline to design workflows that both protect customers and keep their experience seamlessly. You’ll thrive here if you enjoy asking “what if?” — what if attackers shift their tactics, what if a new payment method introduces risk, what if a simpler workflow could reduce friction without losing protection. Your work will directly shape how we protect our customers across money movement, account origination, and card transactions, and you’ll have the freedom to experiment, iterate, and turn insights into impactful strategies. Key Responsibilities: Proactively design, test, implement, and optimize rules for fraud and AML detection across origination, money movement, card, and suspicious activity monitoring. Manage rule libraries, ensuring governance, monitoring, and compliance alignment. Run experiments and pilot new approaches to detect emerging fraud and AML typologies. Collaborate with Data Science to translate fraud patterns and AML scenarios into model features. Partner with Fraud & AML Operations for case feedback and validation of coverage. Define and manage fraud/AML workflows (queues, alerts, escalation paths). Evaluate external fraud and AML data providers for enrichment opportunities. Provide fraud and AML insights, typology analysis, and strategy recommendations to leadership. Partner with Product, Engineering, and Commercial teams to embed proactive fraud and AML strategies into the platform and client dashboards. 5+ years in fraud or AML strategy, risk management, or analytics within financial services/fintech/merchants. Strong knowledge of payment fraud schemes, money laundering typologies, and suspicious activity monitoring. Experience with rule engines, case management, AML monitoring systems, and workflow design. Proficiency in SQL, analytics, and dashboarding tools. Creative, proactive problem solver who thrives in anticipating new risks. Bachelor’s degree in STEM and Economics field required. PTO, Stock Option, Health Benefits

Own and optimize a 12-month event and field marketing calendar aligned to GTM and revenue goals. Collaborate with various teams to deliver high-impact programs and manage logistics for flawless attendee experiences. | 5-7 years of experience in running event and/or field marketing programs in B2B technology is required. The candidate should have a passion for events, strong project management skills, and be a collaborative leader. | DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide a significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe. Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us! Position Overview DataVisor is seeking a strategic, hands‑on Event & Field Marketing Senior Manager with a strong B2B growth mindset to elevate our global event program and field campaigns. Working closely with our Event team—as well as Sales, Product Marketing, Demand Generation, and Design—you will build an integrated roadmap that drives pipeline, deepens customer relationships, and amplifies our market voice. Key Responsibilities Own and optimize a 12‑month event and field marketing calendar aligned to GTM and revenue goals. Craft differentiated messaging for each event, grounded in competitive insights and industry trends. Collaborate daily with the Event team, Sales, PMM, Demand Gen, and Design to deliver high‑impact programs. Pilot new formats and technologies with a growth mindset; iterate quickly based on performance data. Manage budgets, vendors, logistics, and on‑site execution to ensure flawless attendee experiences. Secure and nurture customer and partner participation—joint sessions, success stories, VIP events. Track pipeline influence and ROI; report insights and optimize future events for maximum impact. Document best practices and mentor teammates to foster a self‑driven, collaborative culture. 5–7 years running event and/or field marketing programs in B2B technology, with a proven record of converting campaigns into pipeline and revenue. Passion for events and experimentation—eager to test new formats, technologies, and ideas. Exceptional storyteller able to distill complex technical value into concise, memorable messages. Growth mindset with a bias for action—comfortable piloting initiatives, measuring impact, and iterating quickly. Self‑starter who thrives in fast‑moving environments; able to prioritize, meet deadlines, and deliver results with minimal oversight. Collaborative leader skilled at building trust and alignment across Sales, Product Marketing, Demand Gen, Design, and executive stakeholders. Strong project‑management skills: budget ownership, vendor negotiation, timeline management, and on‑site execution. Data‑driven operator proficient in Salesforce, HubSpot/Marketo, and event‑tech platforms such as Cvent or Splash. Polished communicator—confident presenting to senior leadership, customers, and large external audiences. Willingness to travel for trade shows, field events, and customer engagements. Why Join Us? Opportunity to work on impactful projects that protect businesses from risk loss Collaborate with a diverse and talented team of experts in AI and machine learning Enjoy a flexible, supportive work environment with opportunities for professional growth Competitive compensation and benefits package Stock options, Medical insurance, 401K, PTO