SRS Distribution Inc.

Compensation

Full Description

Position Purpose: The Senior Data Scientist is responsible for designing and implementing advanced machine learning and optimization models to support business decision-making in key areas such as sales, operations, and pricing. This role will lead projects, mentor junior team members, and contribute to enterprise-wide GenAI initiatives. The ideal candidate brings strong technical expertise, business acumen, and the ability to communicate insights effectively to stakeholders at all levels. Key Responsibilities: Design and implement advanced ML models, optimization solutions, and statistical analyses to solve complex business problems Lead small-to-medium scale data science projects from ideation to deployment Mentor and provide technical guidance to junior data scientists Prototype and deploy GenAI and LLM-based solutions in enterprise applications Collaborate with cross-functional teams including operations, product, and engineering to ensure successful model adoption Monitor and evaluate model performance; conduct A/B testing and experimental design for continuous improvement Communicate technical findings and data-driven recommendations to both technical and executive stakeholders Direct Manager/Direct Reports: Direct manager: Sr. Director of Applied AI Direct reports: No direct reports but expected to mentor senior data scientists and lead cross-functional project teams Travel Requirements: Occasional travel may be required (<10%), primarily for team collaboration or business meetings Physical Requirements: Standard office work including prolonged periods at a computer and attending meetings (virtual/in-person) Ability to work effectively in a hybrid environment Working Conditions: Standard office environment Minimum Qualifications: Master’s degree in Data Science, Statistics, Computer Science, or a similar quantitative discipline At least 5 years of experience in applied data science roles Strong understanding of supervised, unsupervised, deep learning, and reinforcement learning techniques Proficient in model deployment using ML frameworks such as TensorFlow, PyTorch, and MLflow Solid grasp of experimental design, statistical inference, and A/B testing methodologies Preferred Qualifications: PhD in Statistics, Machine Learning, Applied Mathematics, or a related field Experience delivering end-to-end data science solutions to solve real-world business problems Familiarity with MLOps practices and lifecycle management Experience applying GenAI technologies in enterprise use cases Strong ability to distill complex analyses into executive-level presentations and recommendations Minimum Education: Master’s degree in a relevant quantitative or technical field Preferred Education: PhD in a quantitative field such as Statistics, Machine Learning, or Applied Mathematics Minimum Years of Work Experience: 5+ years in applied data science, machine learning, or similar roles Certifications: Not required, but relevant certifications (e.g., Microsoft AI-900 certification, TensorFlow Developer Certificate) are a plus. Competencies: Strong technical expertise in machine learning and data science Effective leadership and mentoring skills Strong communication and presentation abilities Business acumen with the ability to align data science work to strategic objectives Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch) Familiarity with data engineering workflows and cloud-based deployments Innovative thinking, especially in applying GenAI in business contexts Work Location: Hybrid – 7440 S. Hwy 121, McKinney, TX 75070 Position Purpose: The Senior Data Scientist is responsible for designing and implementing advanced machine learning and optimization models to support business decision-making in key areas such as sales, operations, and pricing. This role will lead projects, mentor junior team members, and contribute to enterprise-wide GenAI initiatives. The ideal candidate brings strong technical expertise, business acumen, and the ability to communicate insights effectively to stakeholders at all levels. Key Responsibilities: Design and implement advanced ML models, optimization solutions, and statistical analyses to solve complex business problems Lead small-to-medium scale data science projects from ideation to deployment Mentor and provide technical guidance to junior data scientists Prototype and deploy GenAI and LLM-based solutions in enterprise applications Collaborate with cross-functional teams including operations, product, and engineering to ensure successful model adoption Monitor and evaluate model performance; conduct A/B testing and experimental design for continuous improvement Communicate technical findings and data-driven recommendations to both technical and executive stakeholders Direct Manager/Direct Reports: Direct manager: Sr. Director of Applied AI Direct reports: No direct reports but expected to mentor senior data scientists and lead cross-functional project teams Travel Requirements: Occasional travel may be required (<10%), primarily for team collaboration or business meetings Physical Requirements: Standard office work including prolonged periods at a computer and attending meetings (virtual/in-person) Ability to work effectively in a hybrid environment Working Conditions: Standard office environment Minimum Qualifications: Master’s degree in Data Science, Statistics, Computer Science, or a similar quantitative discipline At least 5 years of experience in applied data science roles Strong understanding of supervised, unsupervised, deep learning, and reinforcement learning techniques Proficient in model deployment using ML frameworks such as TensorFlow, PyTorch, and MLflow Solid grasp of experimental design, statistical inference, and A/B testing methodologies Preferred Qualifications: PhD in Statistics, Machine Learning, Applied Mathematics, or a related field Experience delivering end-to-end data science solutions to solve real-world business problems Familiarity with MLOps practices and lifecycle management Experience applying GenAI technologies in enterprise use cases Strong ability to distill complex analyses into executive-level presentations and recommendations Minimum Education: Master’s degree in a relevant quantitative or technical field Preferred Education: PhD in a quantitative field such as Statistics, Machine Learning, or Applied Mathematics Minimum Years of Work Experience: 5+ years in applied data science, machine learning, or similar roles Certifications: Not required, but relevant certifications (e.g., Microsoft AI-900 certification, TensorFlow Developer Certificate) are a plus. Competencies: Strong technical expertise in machine learning and data science Effective leadership and mentoring skills Strong communication and presentation abilities Business acumen with the ability to align data science work to strategic objectives Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch) Familiarity with data engineering workflows and cloud-based deployments Innovative thinking, especially in applying GenAI in business contexts Work Location: Hybrid – 7440 S. Hwy 121, McKinney, TX 75070 Not the right job for you? Register your details at the 'Introduce Yourself' link (top right) and we'll be in touch! Job Location: SRS Distribution - McKinney 7440 State Highway 121 McKinney, TX 75070-3104 Equal Opportunity Employer. Veteran Friendly Employer. SRS Distribution believes in hiring military veterans at any level for any position. We know your service trained you in many of the areas we value, such as; leadership, teamwork, performance, integrity, and safety. If your experience matches our requirements, we want you to apply today. Competitive salaries for all team members paid weekly 401(k) Retirement Plan with company matching Paid Vacation, Sick Time, Holidays, Birthday, and Floating Holidays Paid Parental Leave Medical, Dental and Vision Benefits Flexible and Dependent Care Spending Accounts Company paid Life insurance and Short-Term Disability Additional Life Insurance and Long-Term Disability also offered Safety Program with Bonuses for our Drivers Employee Referral Bonus Program SRS Distribution Inc., a wholly owned subsidiary of The Home Depot, consists of a family of industry-leading, independent roofing distributors. SRS has grown rapidly through acquisitions and the opening of multiple new locations since the February 2008 inception. This continual growth has established SRS as one of the fastest growing building products distribution companies in the U.S. The goal of SRS is to form the strongest national network of independent roofing and building product distributors with the most talented team of people working together to deliver the industry's best products and services. In addition to our commitment to customer focus, SRS strives to become the preferred employer in the industry with highly motivated and engaged employees operating in an entrepreneurial culture where the corporate office works for the field and not the reverse. Make money, have fun and give back with us! Find out more at www.srsdistribution.com. As an Equal Employment Opportunity (EEO) employer SRS Distribution Inc., including all its subsidiaries, provides job opportunities to qualified individuals without regard to actual or perceived race, color, creed, religion, national origin, sex, gender, age, disability, gender identity, sexual orientation, citizenship status, uniform service, veteran status, marital status, genetic information, physical or mental disability, or any other characteristic in accordance with applicable federal, state, and local EEO laws. If you are an individual with a disability or a disabled veteran and require a reasonable accommodation in applying for any posted position, please contact Human Resources at US: 855.556.3221, or by email to: HR@Help.SRSDistribution.com with the nature of your accommodation request and include the Business name, location and title of the job opening. Please allow one (1) business day for a reply. All candidates for employment must successfully complete pre-employment drug testing (where applicable) and background verification before employment is finalized.