Staff Data Scientist, Growth Analytics

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of the analytical strategy for the complete marketing funnel, encompassing marketable lives, lead generation, omni-channel engagement strategy, visit completion, and re-engagement. This responsibility includes our call center operations (outbound representative allocation, inbound referral scheduling, ZCC data) and member lifecycle (performance of Customer.io journeys, reactivation efforts, and optimization of initial visit completions).

• Oversee the product analytics domain: onboarding funnel, sign-up conversion, in-app engagement, and the member experience leading to the first appointment. Collaborate with the top-of-funnel product team as their embedded analytical lead, participating in product meetings and co-managing the product analytics roadmap.

• Act as the executive-facing custodian of the marketing and product performance narrative: clarifying shifts in marketable lives, funnel conversion, and initial visit completions, identifying the factors that influenced these changes, and recommending areas for further investment.

• Design and manage Foodsmart's experimentation program across marketing and product sectors, covering test design, causal inference methods, readout discipline, and the process for stakeholder-driven test proposals. Take ownership of StatSig implementation and serve as the resident expert on experiment instrumentation, StatSig setup, and result interpretation.

• Manage and enhance our attribution framework, which includes scheduling episode attribution, multi-touch attribution, and media mix modeling as Foodsmart's channel portfolio expands.

• Collaborate with Growth Marketing leadership as the embedded analytical lead: participating in marketing meetings, co-managing the analytics roadmap, and translating insights into actionable strategies.

• Manage and refine the dbt data models for the marketing and product domains — from raw source modeling to mart-layer metrics — ensuring data integrity, test coverage, thorough documentation, and a reliable semantic layer for self-service functionalities. This is a fundamental expectation of this role, rather than a secondary one.

• Incorporate context into our semantic layer and BI environment (Omni) so that stakeholders and AI agents can consistently self-serve insights across the marketing and product funnels. You consider context engineering — crafting descriptions, defining metrics, and curating exposed data — as a primary aspect of your responsibilities.

• Lead the narrative, not just the numbers — convert findings into clear, actionable recommendations for executive and marketing leadership audiences.

• Elevate the analytics team’s standards in key areas central to this role — experimentation design, dbt modeling patterns, and context engineering. While you do not have direct reports, you act as a technical leader: establishing best practices, reviewing work, and enhancing the capabilities of the team around you.

⛳️ Requirements

• Bachelor's degree, preferably in a quantitative or technical discipline (e.g., Economics, Statistics, Computer Science, Operations Research, Applied Mathematics); a Master's degree is an advantage.

• 8+ years of experience in data science, analytics, or experimentation, with a proven ability to deliver measurable impacts on growth, acquisition, or lifecycle outcomes.

• Extensive, practical expertise in experimentation and causal inference. You have designed and analyzed rigorous tests (A/B, quasi-experimental, geo-lift) and can substantiate your methodological choices when challenged.

• Strong background in attribution modeling (scheduling episode, multi-touch attribution, media mix modeling) and a clear perspective on the trade-offs between different approaches.

• Experience managing lifecycle analytics, ideally including hands-on experience with Customer.io, Braze, Iterable, or a similar platform.

• Practical experience with product analytics instrumentation — event tracking, funnel analysis, and experimentation platforms (Statsig, Amplitude, Mixpanel, or similar) — along with a clear viewpoint on what constitutes effective product measurement infrastructure.

• Familiarity with call center or contact center analytics is a plus. We utilize Zoom Contact Center (ZCC) for our outbound and inbound scheduling teams.

• Expert proficiency in SQL and strong proficiency in Python (pandas, scikit-learn, statsmodels, etc.).

• Extensive, production-level experience with dbt — including source and mart-layer modeling, testing, documentation, and semantic layer design. You have overseen a dbt project from start to finish, not merely contributed to one.

• Experience with context engineering for BI and AI self-service: composing semantic layer definitions, metric descriptions, and data model documentation that facilitate reliable AI-assisted querying (Omni, Looker, or equivalent).

• Proven fluency with AI-native developer and analyst tools — Claude, Claude Code, Cursor, Hex AI Agent, Omni AI, or similar — utilized in production analytical workflows.

• Experience in marketplace business models and/or adjacent to healthcare, Medicaid, or similarly regulated domains is beneficial but not mandatory.

• Exceptional communication skills. You can simplify complex models, test outcomes, and funnel diagnostics into clear, actionable recommendations for executive and marketing leadership audiences.

🏝️ Benefits

• Remote-First Company

• Unlimited PTO

• Flexible & remote location

• Healthcare Coverage (Medical, Dental, Vision)

• 401k & bonus

• Registered Dietitian Sessions