Director, Member Data Science

### **About Foodsmart:** Foodsmart is the leading Foodcare platform in the U.S., built to deliver nutrition-driven healthcare at scale. Powered by a national network of Registered Dietitians, Foodsmart combines personalized clinical nutrition care, behavior change tools, and food benefits to improve member health outcomes while lowering healthcare costs. Our platform is designed to foster healthier food choices, drive lasting behavior change, and deliver sustainable health outcomes. Through our highly personalized, digital platform, we guide more than 3 million members—including those in employer-sponsored health plans, regional and national Medicaid managed care organizations, Medicare Advantage plans, and commercial insurers—on a tailored journey to eating well while saving time and money. Foodsmart seamlessly integrates dietary assessments and nutrition counseling with online food ordering and cost-effective meal planning for the entire family, optimizing ingredients both at home and on the go. We partner with national and regional retailers across the U.S., many of whom accept SNAP/EBT, making healthier food more accessible. Additionally, we assist members with SNAP enrollment and management, providing tangible access to nutritious food. In 2024, Foodsmart secured a $200 million investment from TPG’s Rise Fund, which supports entrepreneurs dedicated to achieving the United Nations’ Sustainable Development Goals. This investment helps us expand our reach, particularly to low-income workers who are disproportionately affected by diet-related diseases. At Foodsmart, our mission is to make nutritious food accessible and affordable for everyone, regardless of economic status. We are committed to a set of core values that shape our culture and work environment: 👥 Customer First - You start with the member and work backwards. 🚀 Make It Happen - You act with urgency, use data, and hold high standards. 🤝 One Team - You collaborate with respect and commit as a group. Whether you're a dietitian, a commercial leader, or a technologist, working at Foodsmart means being part of a team that is passionate, supportive, and driven by a shared purpose. Join us in transforming the way people access and enjoy healthy food. ### **About the Role:** We’re looking for a Director, Member Data Science to own the analytics behind the entire path a member takes with Foodsmart, from first contact, through activation, to long-term retention. You’ll partner closely with Marketing, Product, and Clinical Operations along the way. This is a high-impact, domain-owning leadership role reporting to the VP of Analytics & Data Science. You’ll be the executive-facing voice on member funnel and retention performance, lead our experimentation and causal inference program, and build the attribution and lifecycle models that shape how Foodsmart invests across the member journey. You’ll partner directly with senior company leadership as the analytical voice understanding the member journey. You’ll lead a small team while staying hands-on yourself. This is a meaningfully technical role, not a pure people-management seat: we need someone who can build and review the models directly, operate as a trusted thought partner to executive stakeholders, and coach the team toward increasingly independent ownership. As this area grows, we expect that growth to come from leverage, not just headcount: real scale will come from how well you and your team use AI agents and tooling to extend your reach. If you’re energized by getting more out of a small team through scale of impact rather than by managing a bigger one, this is built for you. This is a full-stack data science leadership role. We’re not looking for a pure statistician or a pure analytics engineer. We need someone who operates across the entire analytical stack, from dbt source models and semantic layer design, to BI dashboards and self-service tooling, to predictive modeling, causal inference, and optimization work. At Foodsmart, durable insight requires owning the data foundation it sits on, and impactful models require the communication infrastructure to drive decisions. We expect this person to be strong across all of it, and to instill that same standard in the team they lead. We’re a small, flat, fast-moving team that leans hard into AI-native tooling. We use Hex and its AI Agent for analysis, and Omni with deep context engineering to power stakeholder self-service. We’re actively expanding our use of Claude Code across our workflows, and we want someone who treats these tools as force multipliers for their own output and their team’s, not someone who sees analytics as a hand-cranked request queue. ### You will: - Own the analytical strategy for the end-to-end marketing funnel across both activation and retention: from marketable lives to lead generation to omni-channel engagement strategy, to visit completion, re-engagement, and the reactivation campaigns that bring lapsed members back into their care journey. This includes our call center function (outbound rep allocation, inbound referral scheduling, ZCC data) and member lifecycle ( journey performance). - Own the product analytics domain across both activation and retention: onboarding funnel, sign-up conversion, in-app engagement through a member’s completed first appointment, and the ongoing booking and in-app experience that shapes whether members keep coming back. Partner with the product team as their embedded analytical lead, attending product cadences and co-owning the product analytics roadmap. - Serve as the executive-facing owner of the member funnel and retention performance narrative: explaining why marketable lives, funnel conversion, initial visit completion, and retention moved, what levers drove the result, and what to double down on. Partner directly with senior leaders as the analytical voice for the member journey. - Design and lead Foodsmart’s experimentation program across marketing, product, and retention, including test design, causal inference methods, readout discipline, and the intake process for stakeholder-driven test ideas. Own the StatSig implementation and serve as the internal expert on experiment instrumentation, StatSig configuration, and results interpretation. - Own and evolve our attribution framework, including scheduling episode attribution, multi-touch attribution, and media mix modeling as Foodsmart’s channel portfolio grows. - Partner with Clinical Operations leadership, whose Registered Dietitian network is a key driver of member retention. - Own and evolve the dbt data models across marketing, product, and retention, from raw source modeling through metrics, ensuring data quality, test coverage, documentation, and a semantic layer that makes self-service trustworthy. This is a core craft expectation of this role, not a secondary responsibility. - Engineer context into our semantic layer and BI environment (Omni) so that stakeholders and AI agents can reliably self-serve answers across the member journey. You treat context engineering (writing descriptions, defining metrics, curating what’s exposed) as a first-class part of your job. - Lead and develop a small team: setting technical direction, reviewing work, coaching toward increasingly independent ownership of their part of the member journey, and helping the team find real leverage through AI tooling rather than doing more manual work. ### You are: - An operator who thrives in flat, fast-moving teams. You need minimal guidance to drive outcomes and default to taking ownership rather than waiting for direction. - A domain-owning leader who is comfortable being the single point of accountability for a critical, company-level outcome and the executive-facing voice on its performance. - A rigorous experimentalist who treats causal inference as a core craft, not a buzzword. You have a point of view on what makes a test trustworthy and how to teach causal thinking to business partners. - A strategic partner who can translate a high-level business problem into a concrete analytical roadmap and influence senior leaders, including C-level executives, across product, marketing, clinical, and finance. - A full-stack analytics practitioner, strong across analytics engineering (dbt, semantic layer), business intelligence and dashboarding, and data science (predictive modeling, causal inference, optimization). You don’t silo into pure stats/Python work, and you understand that durable insight requires owning the data foundation, not just the models on top of it. - Deeply fluent with AI-native tooling. You see tools like Claude, Claude Code, and in-BI AI agents as a core part of how you and your team get leverage, and you have a point of view on how to engineer the context and semantic layer that makes AI-driven self-service trustworthy. - Genuinely energized by scaling a small team’s output through AI rather than through more headcount. You’d rather solve “how do we get 3x the leverage out of this team” than “how do I get budget for 2 more hires,” and you want the person you manage to feel that same energy. - A capable, motivated people leader who wants to stay predominantly hands-on. This is not a pure management-track role. We’re looking for someone who leads by building and reviewing alongside their team, not by stepping back from the work. ### You have: - Bachelor’s degree, ideally in a quantitative or technical field (e.g., Economics, Statistics, Computer Science, Operations Research, Applied Mathematics); Master’s degree is a plus. - 12+ years of experience in data science, analytics, or experimentation, with a proven track record of driving measurable impact on growth, acquisition, or lifecycle outcomes. 4+ years leading teams. - Experience partnering directly with senior and executive stakeholders (VP-level and above) as the analytical voice for a business area, ideally including some experience leading or mentoring other data scientists or analysts. - Deep, hands-on expertise in experimentation and causal inference. You have designed and interpreted rigorous tests (A/B, quasi-experimental, geo-lift) and can defend methodology choices under scrutiny. - Strong background in attribution modeling (scheduling episode, multi-touch attribution, media mix modeling) and a clear point of view on the tradeoffs between approaches. - Experience owning lifecycle analytics, ideally including hands-on work with , Braze, Iterable, or a similar platform. - Hands-on experience with product analytics instrumentation: event tracking, funnel analysis, and experimentation platforms (Statsig, Amplitude, Mixpanel, or equivalent). You have a point of view on what good product measurement infrastructure looks like. - Experience with call center or contact center analytics is a plus. We leverage Zoom Contact Center (ZCC) for our outbound and inbound scheduling teams. - Expert-level proficiency in SQL and strong proficiency in Python (pandas, scikit-learn, statsmodels, etc.). - Deep, production-level experience with dbt, including source and mart-layer modeling, testing, documentation, and semantic layer design. You have owned a dbt project end-to-end, not just contributed to one. - Experience with context engineering for BI and AI self-service: writing semantic layer definitions, metric descriptions, and data model documentation that enables reliable AI-assisted querying (Omni, Looker, or equivalent). - Proven fluency with AI-native developer and analyst tooling (Claude, Claude Code, Cursor, Hex AI Agent, Omni AI, or equivalent) used in production analytical workflows. - Experience working in marketplace business models and/or adjacent to healthcare, Medicaid, or a similarly regulated domain is a plus but not required. - Excellent communication skills. You can distill complex models, test results, and funnel diagnostics into clear, actionable recommendations for executive, product, and marketing-leadership audiences.