Senior Data Scientist

Responsibilities

• Own and deliver high-impact data science initiatives, from problem definition and data exploration to modeling, validation, and productionization, driving measurable improvements in customer experience and business metrics.
• Partner closely with Product, Engineering, and Analytics to shape roadmaps, define success metrics, and translate ambiguous business problems into well-scoped analytical or modeling solutions.
• Partner with Engineering and DevOps to deploy, operate, and scale ML workloads using cloud-native infrastructure and MLOps tooling (e.g., AWS SageMaker, Lambda, S3, ECR, Docker, Kubernetes).
• Design, build, and iterate on statistical models, machine learning systems, and decision frameworks (e.g., personalization, ranking, forecasting, experimentation analysis).
• Lead rigorous experimentation and measurement practices, including A/B test design, hypothesis formulation, metric selection, causal inference, and interpretation of results.
• Communicate insights, trade-offs, and recommendations clearly to both technical and non-technical stakeholders, influencing decisions at the pod and org level.
• Ensure high standards of quality and reliability in data science outputs through code reviews, model validation, documentation, and monitoring.
• Proactively identify opportunities and risks in data, modeling, or experimentation approaches, and drive improvements that enhance scalability, accuracy, and long-term impact.
• Mentor and support other data scientists through technical guidance, feedback, and best-practice sharing, without direct people management responsibility.

Qualifications

• 5+ years of experience in data science, applied machine learning, or a related quantitative role, with demonstrated ownership of end-to-end projects.
• Strong grounding in ML, statistics, experimentation and data analysis, including hypothesis testing, causal reasoning, and metric design.
• Experience building and deploying production-grade models or analytical systems in collaboration with engineering teams, including hands-on experience with cloud-based ML infrastructure (e.g., AWS SageMaker, Lambda, S3, ECR) and containerized workflows (Docker, Kubernetes).
• Proven experience designing, analyzing, and interpreting A/B tests in production environments, aligned to business or product goals, including defining success metrics and guarding against common statistical pitfalls.
• Able to work effectively with cross-functional partners (Product, Engineering, Analytics, Design, Data Engineering), translating between business context and technical solutions.
• Strong problem-framing and prioritization skills, particularly in ambiguous or under-specified problem spaces.
• Proficiency in SQL and Python, with experience using modern data and ML tooling.
• Ownership mindset: proactively identifying problems worth solving, taking accountability for outcomes, and driving initiatives forward independently.

Preferred

• Hands-on experience with search, personalization, recommendations, ranking, or lifecycle modeling.
• Experience with MLOps best practices, including model versioning, CI/CD for ML, monitoring, and operating models in containerized and orchestrated environments (Docker, Kubernetes).
• Experience in e-commerce, marketplace, or subscription-based businesses.
• Familiarity with working in environments with moderate technical debt or evolving data foundations.
• Experience defining and owning metrics, experimentation frameworks, or model performance monitoring in production.
• Demonstrated ability to influence beyond immediate project scope, shaping best practices, standards, or strategy across teams.

Benefits

Comprehensive health benefits (medical, dental, vision, life and disability)

Competitive salary (DOE) + equity

401k Employer Match

9 Days of Observed Holidays

Flexible Paid Time Off

Subsidized ClassPass Membership with access to fitness classes and wellness and beauty experiences

Free Thrive Market membership with exclusive employee discount

Coverage for Life Coaching & Therapy Sessions on our holistic mental health and well-being platform

At Thrive Market, our goal is to be a diverse and inclusive workplace that is representative, at all job levels, of the members we serve and the communities we operate in.