Senior Data Scientist - Marketing

Role overview

An experienced senior data scientist is needed to partner with marketing, finance, retail, and product to translate marketing data into measurable business decisions. The role combines rigorous model development with the design of decision systems, dashboards, and experimentation frameworks that help a consumer health company allocate spend more efficiently and strengthen revenue measurement foundations.

Responsibilities

- Build optimization and forecasting models for upper-funnel marketing, including spend allocation, channel mix, budget pacing, audience strategy, and revenue impact. - Design and operationalize decision systems that move the business from static reporting to repeatable, data-informed action, including recommendation engines and scenario planning tools. - Lead experimentation and causal measurement across marketing programs, separating signal from noise across channels, campaigns, and retail partnerships. - Unify marketing, revenue, retail, and product data into trusted foundations, building dashboards and recurring analytical products that surface funnel and campaign health. - Partner with data engineering to improve data quality, instrumentation, metric definitions, and pipeline reliability across the marketing data ecosystem. - Translate complex analyses into clear recommendations for executive and non-technical stakeholders, influencing roadmap, budget, and growth strategy.

Requirements

- 6+ years of experience in data science, machine learning, or advanced analytics with a track record of owning high-impact business problems end to end. - Strong domain experience supporting marketing, growth, retail, or other go-to-market functions in consumer, e-commerce, retail, or digital businesses. - Hands-on experience building spend optimization, channel measurement, media mix or incrementality, propensity, or upper-funnel decisioning models. - Strong proficiency in SQL (dbt) and Python, with experience building analytical data models and production-quality measurement systems. - Familiarity with modern data and ML tooling such as Databricks, AWS, dbt, or Snowflake. - Demonstrated ability to communicate complex analytical concepts clearly and partner effectively with distributed, cross-functional teams.

Nice to have

- Experience in e-commerce, DTC, retail, or omnichannel growth environments. - Experience with marketing mix modeling, incrementality testing, attribution, or budget planning workflows. - Background connecting marketing, retail, and commercial performance data to downstream revenue outcomes. - Experience in digital health, consumer technology, or wearable products. - Track record mentoring data scientists and shaping cross-functional analytical roadmaps.

Benefits and work setup

- Competitive salary with market-based pay ranges that vary by US location tier, ranging from roughly $147,900 - $203,000 annually, plus equity. - Health, dental, vision insurance and mental health resources, plus a product of their own and discounts for friends and family. - 20 days of paid time off, 13 paid holidays, and 8 days of flexible wellness time off, alongside paid sick leave and parental leave.