Staff Data Scientist, Growth Analytics

Foodsmart

1d•Remote

About The Position

Foodsmart is seeking a Staff Data Scientist to lead the analytical strategy for its Member growth engine, encompassing both marketing and product analytics. This role involves owning the end-to-end acquisition funnel, from marketable lives to initial visit completion, across outbound and inbound channels. On the product side, the focus is on the member-facing funnel, including onboarding, sign-up conversion, and the in-app experience up to the first completed appointment. This is a high-impact, domain-owning role reporting to the VP of Analytics & Data Science. The individual will be responsible for the executive narrative on marketing and product funnel performance, leading the experimentation and causal inference program, and building attribution, lifecycle, and product analytics models. A key aspect of the role is contributing to the event tracking infrastructure and product analytics foundation, including Statsig implementation, to enable rigorous product experimentation. This is a full-stack data science role requiring expertise across the entire analytical stack, from dbt models and semantic layer design to BI dashboards, predictive modeling, causal inference, and optimization. The team utilizes AI-native tooling such as Hex, Omni, Claude, and Claude Code, and expects the candidate to leverage these tools as force multipliers. The role emphasizes owning the data foundation and building communication infrastructure to drive decisions, rather than operating as a request queue.

Requirements

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.
8+ years of experience in data science, analytics, or experimentation, with a proven track record of driving measurable impact on growth, acquisition, or lifecycle outcomes.
Deep, hands-on expertise in experimentation and causal inference, including designing and interpreting rigorous tests (A/B, quasi-experimental, geo-lift).
Strong background in attribution modeling (scheduling episode, multi-touch attribution, media mix modeling).
Experience owning lifecycle analytics, ideally including hands-on work with Customer.io, 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).
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.
Experience with context engineering for BI and AI self-service: writing semantic layer definitions, metric descriptions, and data model documentation.
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.
Excellent communication skills; ability to distill complex models, test results, and funnel diagnostics into clear, actionable recommendations for executive and marketing-leadership audiences.

Nice To Haves

Experience with call center or contact center analytics is a plus. We leverage Zoom Contact Center (ZCC) for our outbound and inbound scheduling teams.
Experience working in marketplace business models and/or adjacent to healthcare, Medicaid, or a similarly regulated domain is a plus but not required.

Responsibilities

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, including call center functions and member lifecycle 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.
Serve as the executive-facing owner of the marketing and product performance narrative, explaining performance drivers and recommending strategies.
Design and lead Foodsmart's experimentation program across both marketing and product, including test design, causal inference methods, readout discipline, and StatSig implementation.
Own and evolve our attribution framework, including scheduling episode attribution, multi-touch attribution, and media mix modeling.
Partner with Growth Marketing leadership as the embedded analytical lead, co-owning the analytics roadmap and driving insight into action.
Own and evolve the dbt data models for the marketing and product domains, ensuring data quality, test coverage, documentation, and a trustworthy semantic layer.
Engineer context into our semantic layer and BI environment (Omni) for stakeholder and AI agent self-service.
Translate findings into clear, actionable recommendations for executive and marketing leadership audiences.
Raise the bar for the analytics team on craft areas like experimentation design, dbt modeling patterns, and context engineering, acting as a technical leader.