Director, Data Science & Machine Learning

ABOUT THRIVE MARKET

Thrive Market was founded in 2014 with a mission to make healthy and sustainable living easy and affordable for everyone. As an online, membership-based market, we deliver the highest quality healthy, and sustainable products at member-only prices, while matching every paid membership with a free one for someone in need. Every day, we leverage innovative technology and member-first thinking to help our over 1,700,000+ members find better products, support better brands, and build a better world in the process. We are also a Certified B Corporation, a Public Benefit Corporation, and a Climate Neutral Certified company.

Join us as we bring healthy and sustainable living to millions of Americans in the years to come.

The Role

Thrive Market is looking for a Director of Data Science & Machine Learning to lead the company's ML organization. Thrive Market exists to make healthy and sustainable living easy and affordable. That mission is fundamentally a personalization problem, connecting the right member with the right products, at the right moment, in a way that builds lasting habits and loyalty. Machine learning is the most powerful tool available to solve that problem at scale. This role sits at the intersection of applied science, engineering, and product strategy.

Thrive Market is moving toward a dynamic layout architecture. Rather than relying on static templates and generic carousels, the vision is for every member to see a personalized storefront; product recommendations, search results, promotions, and content all dynamically assembled by ML-powered systems. This leader will be the driving force behind making that vision a reality.

You will lead a team of Senior Data Scientists and also a group of cross-functional engineers to deliver ML-assisted shopping from ML model to customer experiments. The vision is for models to move from development to live experiments in weeks rather than quarters. This role would oversee the hiring of multiple team members (Sr. Data Scientist, ML Data Engineer, Fullstack Engineer, Mobile Engineer). This is a hands-on leadership role: you will set the technical direction, build and scale the team, partner deeply with Product, Engineering, and business stakeholders, and ensure ML is embedded across the platform, not siloed as a service function.

Requirements

ML Strategy & Organizational Leadership

• Define and execute the ML roadmap for Thrive Market, aligning machine learning investments with business priorities across search, discovery, personalization, growth, and operations.
• Build, scale, and mentor a high-performing ML team spanning data science, ML engineering, and analytics.
• Serve as the primary ML voice in product and engineering leadership forums, translating business objectives into ML-solvable problems and communicating technical trade-offs to non-technical stakeholders.

Personalization & Ranking Systems

• Own the strategy and execution of Thrive Market's server-driven personalization, driving dynamically assembled, per-member experiences across all major site surfaces.
• Define and evolve the overall recommendations strategy - both global (site-wide signals and ranking) and localized (surface-specific, contextual, and intent-driven), ensuring recommendations compound in relevance and business impact over time.
• Own the ML search strategy end-to-end: relevance, ranking, personalization, and retrieval to continuously improve member experience and engagement through iterative modeling and experimentation.

ML Decision Systems & Business Impact

• Develop and evolve production ML decision systems across member lifecycle, demand forecasting, and segmentation to be used across finance, growth, and operations to guide domain strategy, capital allocation, and retention.
• Partner with cross-functional teams (Product, Marketing, Merchandising, Finance) to identify high-impact ML applications and ensure models are integrated into business workflows, not just prototyped.

ML Platform & Infrastructure

• Strengthen ML platform foundations: model deployment, feature pipelines, validation frameworks, monitoring, and experiment velocity.
• Drive adoption of best practices for ML reliability-automated testing, model health monitoring, graceful degradation, and observability.
• Enable faster iteration cycles across the ML team through tooling, infrastructure investment, and process improvements.

Applied GenAI & Innovation

• Lead applied GenAI exploration, including prototyping LLM-powered assistants for shopping, product discovery, and personalization workflows.
• Evaluate emerging ML techniques and tooling, maintaining a pragmatic lens on what delivers member and business value versus what is experimental.

Qualifications

Must-Have

• 8+ years of experience in data science, machine learning, or applied ML engineering, with at least 3 years leading ML teams in a production environment.
• Deep technical expertise in search, retrieval, ranking, and/or reco