foodsmart - Staff Data Scientist, Growth Analytics

• Own the analytical strategy for the end-to-end marketing funnel, from marketable lives to lead generation to omni-channel engagement strategy to visit completion and re-engagement. This includes our call center function (outbound rep allocation, inbound referral scheduling, ZCC data) and member lifecycle (Customer.io journey performance, reactivation, and initial visit completion optimization). • Own the product analytics domain: onboarding funnel, sign-up conversion, in-app engagement, and the member experience through completed first appointment. Partner with the top-of-funnel 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 marketing and product performance narrative: explaining why marketable lives, funnel conversion, and initial visit completion moved, what levers drove the result, and what to double down on. • Design and lead Foodsmart's experimentation program across both marketing and product, 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 Growth Marketing leadership as the embedded analytical lead: attending marketing cadences, co-owning the analytics roadmap, and driving insight into action. • Own and evolve the dbt data models for the marketing and product domains — from raw source modeling through mart-layer 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 marketing and product funnel. You treat context engineering — writing descriptions, defining metrics, curating what's exposed — as a first-class part of your job. • Drive the narrative, not just the numbers — translate findings into clear, actionable recommendations for executive and marketing leadership audiences. • Raise the bar for the analytics team on the craft areas central to this role — experimentation design, dbt modeling patterns, and context engineering. You don't manage anyone, but you operate as a technical leader: establishing best practices, reviewing work, and making the team around you better. • 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 IC who is comfortable being the single point of accountability for a critical business area and the executive-facing voice on its performance. • A rigorous experimentalist who treats causal inference as a core craft, not a buzzword — with 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 across marketing, product, 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) — who doesn't silo into pure stats/Python work and understands 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 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.