Data Scientist

What we’re building and why we’re building it.

Every month, millions of people use Fetch, earning rewards for buying brands they love, and a whole lot more. Whether shopping in the grocery aisle, grabbing a bite at the drive-through or playing a favorite mobile game, Fetch empowers consumers to live rewarded throughout their day. To date, we’ve delivered more than $1 billion in rewards and earned more than 5 million five‑star reviews from happy users.

It’s not just our users who believe in Fetch: with investments from Soft Bank, Univision, and Hamilton Lane, and partnerships ranging from challenger brands to Fortune 500 companies, Fetch is reshaping how brands and consumers connect in the marketplace. When you work at Fetch, you play a vital role in a platform that drives brand loyalty and creates lifelong consumers with the power of Fetch points.

User and partner success are at the heart of everything we do, and we extend that same commitment to our employees.

At Fetch, we value curiosity, adaptability, and the confidence to explore new tools, especially AI, to drive smarter, faster work. You don’t need to be an expert, but you should be ready to learn quickly and think critically. We welcome learners who move fast, challenge the status quo, and shape what’s next, with us. Ranked as one of America’s Best Startup Employers by Forbes for two years in a row, Fetch fosters a people‑first culture rooted in trust, accountability, and innovation.

We encourage our employees to challenge ideas, think bigger, and always bring the fun to Fetch.

Fetch is an equal employment opportunity employer.

AI & Data at Fetch sit at the center of how we understand our business, make decisions, and build intelligent products. The organization operates as an integrated AI & data ecosystem, spanning multiple disciplines, including data engineering, analytics engineering, machine learning, experimentation, and data platforms, all working together to turn data into durable business and customer impact.

Teams operate in complex problem spaces where requirements evolve, tradeoffs are constant, and the right answer is rarely obvious. Success depends on strong technical judgment, comfort with ambiguity, and the ability to gather context and make informed decisions while balancing quality, performance, scalability, and responsible use.

Practitioners across this org contribute hands‑on to production systems, analytical foundations, and intelligent features. You will collaborate closely with product, platform, and engineering partners, help shape standards and best practices, and ensure our AI and data capabilities scale reliably as Fetch grows.

Fetch is at a critical inflection point in how data and science inform the company’s most important decisions. With millions of monthly active users, rich item‑level purchase data, and increasing investment in AI‑driven products like Fetch

GPT, Fetch has an opportunity to establish a rigorous, scalable measurement and causal reasoning foundation that powers pricing, incentives, growth, marketing investment, and financial planning.

We are seeking a Staff Data Scientist to serve as the company‑wide scientific and measurement leader. This role goes beyond traditional analytics or domain ownership. You will define how Fetch measures value, reasons about causality, and translates evidence into executive decisions. You will own core measurement frameworks, architect semantic and metric foundations, and set the scientific quality bar across analytics, experimentation, and strategic modeling.

Within your first year, you will define Fetch’s MAU × ARPU measurement operating system, establish canonical metrics and semantic standards powering Fetch

GPT and executive reporting, and deliver strategic models such as marketing mix, elasticity, and incentive sensitivity that directly inform leadership decisions.

• Define and own Fetch’s company‑level measurement framework anchored in MAU × ARPU.
• Company Measurement and Causal Strategy.
• Establish decision frameworks for pricing, incentives, and value trade‑offs.
• Set standards for evidence quality, uncertainty,…