Senior Data Scientist II, Monetization
Summary
Senior data scientist who owns the scientific and product roadmap for a Monetization domain at Fetch — building advertiser audience products and receipt-based ad measurement from first-party purchase data. A hands-on role combining SQL, Python, statistical modeling, and causal inference with cross-functional leadership alongside Product, Sales, and GTM.
- Own the scientific and product roadmap for your domain, deciding what to build, what to sequence, and what to decline
- Set the standards for how audiences are created, evaluated, and expanded beyond Fetch users
- Make the call on reach–precision and revenue–cost trade-offs, favoring scalable products over one-off customization
- Shape how we combine receipt, partner, panel, and survey data, and decide which data investments are worth making
- Own measurement methodology for complex studies linking ad exposure to receipt-observed purchases
- Define what results can and can’t support, especially when a causal claim or generalization goes beyond the evidence
- Turn bespoke studies into repeatable products
- Build the feedback loop between audiences and measurement, with the holdouts and monitoring to trust what it tells you
- Connect first-party monetization with third-party products, including using audience insights to acquire and engage high-value users
- Lead the scientific case with Sales and GTM, from customer discovery and pilots to positioning and handling buyer objections
- Influence senior stakeholders and commercial commitments with clear, evidence-backed recommendations
- Stay hands-on in SQL, Python, statistical modeling, and causal inference
- Mentor scientists and establish methods that raise quality across the domain
- 8+ years of experience in data science, machine learning, or applied analytics, with demonstrated leadership of complex analytical products in product-driven environments
- Experience defining a scientific or data-product roadmap, and the ability to explain what you prioritized, what you declined, and why
- Experience leading cross-functional delivery with Sales, GTM, Product, and Engineering, including shaping customer pilots and defending product value directly
- A track record of building differentiated datasets or audience products from imperfect sources, with clear trade-offs on coverage, validity, and cost
- Experience with audience expansion, panel calibration, data fusion, or measurement products that held up beyond the original sample
- Ownership of complex causal measurement, including defending your assumptions under scrutiny and changing a recommendation when the evidence fell short
- Judgment on reach–precision and revenue–cost trade-offs, including recognizing when more scale reduced value
- Sustained audience or monetization gains and customer adoption, with measured outcomes used to redirect product strategy
- Evidence of influencing senior stakeholders, such as times when evidence changed a pitch, commitment, or investment
- Hands-on depth in SQL, Python, statistical modeling, and causal inference
- Experience mentoring scientists and establishing reusable methods that improved quality beyond your own work
- Substantial ownership of audience, measurement, or monetization data products in advertising, retail media, market research, consumer panels, or a comparable commercial setting is strongly preferred
- Experience translating market research or quantitative social science into repeatable products and customer or commercial decisions
- A background in political science, survey methodology, econometrics, demography, or another resource-constrained quantitative field