Senior Data Scientist

About Fetch

Fetch helps people live rewarded every day, with a vision to become the rewards destination for everyone. We turn everyday activities into meaningful rewards, whether it’s grocery shopping, grabbing a quick meal, or playing a favorite mobile game. To date, we’ve awarded more than $1 billion in Fetch Points to our users. Each day, more than 13 million receipts are submitted on Fetch, providing visibility into over $212 billion in gross merchandise value. This creates the largest retail-agnostic, SKU-level view of household spending, powering Fetch as an outcomes-based advertising platform that helps brands acquire and retain lifelong consumers.

The Fetch app is available on the App Store and Google Play, with more than 6 million five-star reviews from a highly engaged and loyal user base. It’s not just our users who believe in Fetch: with investments from Softbank, ICONIQ, DST, Greycroft, 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.

About AI & Data at Fetch

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.

About The Role

We are seeking a Senior Data Scientist to serve as a key analytical partner within Fetch, owning complex analyses and measurement frameworks that inform product and business decisions. You will take primary analytical ownership of a product or business area, defining and monitoring core KPIs, identifying opportunities, and using experimentation, statistical modeling, and data-driven recommendations to improve user and business outcomes. You will partner cross-functionally with Product, Engineering, Marketing, and Data Product teams to turn ambiguous business questions into structured analytical approaches and actionable recommendations.

Success in this role requires strong technical judgment, the ability to balance analytical rigor with business urgency, and the ability to connect data and model outputs to the underlying drivers of revenue, cost, and user behavior. Over time, you will take on increasingly sophisticated modeling and business case development while helping strengthen data literacy and analytical rigor across your team.

Responsibilities

Analytics & Modeling

• Independently design and execute complex analyses, statistical models, and measurement frameworks that inform product and business decisions.
• Apply statistical methods such as experimental design, causal inference, predictive modeling, and Bayesian approaches based on the needs of the problem.
• Translate ambiguous business questions into structured analytical approaches, identifying the appropriate metrics, methodologies, and data required.
• Make thoughtful trade-offs between rigor, speed, precision, and practicality based on the business decision at hand.

Business Impact & Experimentation

• Act as the primary analytical owner for a product or business area, defining and maintaining its core KPIs and measurement frameworks.
• Proactively identify opportunities where analytics and experimentation can improve user behavior, revenue, conversion, retention, cost efficiency, or other key outcomes.
• Design and analyze experiments, partnering with Product and Engineering to influence experimentation strategy and decision-making.
• Connect metric movements and analytical findings to underlying business drivers, clearly articulating implications and recommended actions.
• Quantify the impact of product and business initiatives and use those insights to influence roadmap and prioritization decisions.

Collaboration & Influence

• Partner closely with Product, Engineering, Marketing, and Data Product stakeholders to inform team-level product and business decisions.
• Communicate complex analyses through clear narratives and visualizations, including assumptions, trade-offs, confidence levels, and expected business impact.
• Translate technical and analytical concepts for non-technical partners and navigate cross-functional dependencies effectively.
• Increase data literacy by making metrics, analyses, and recommendations accessible and actionable for stakeholders.
• Informally mentor junior data scientists and analysts, helping strengthen their technical judgment and analytical approaches.

Technical Excellence

• Leverage tools and technologies such as Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to conduct and scale analytical work.
• Apply strong practices in experimentation, model validation, reproducibility, and governance.
• Use AI/ML tools thoughtfully to improve analytical workflows, automation, documentation, and anomaly detection while maintaining appropriate validation.

Requirements

Minimum Requirements

• 5+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments.
• Strong expertise in statistical modeling, experimental design, and causal inference.
• Experience owning KPIs, measurement, or analytics for a product or business area and translating findings into actionable recommendations.
• Demonstrated ability to structure ambiguous business problems and connect analytical findings to business drivers such as revenue, cost, conversion, retention, or user behavior.
• Strong proficiency in SQL and at least one programming language, preferably Python.
• Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark.
• Proven ability to communicate complex technical insights, trade-offs, and confidence levels to technical and non-technical stakeholders.
• Ability to work independently while navigating cross-functional dependencies and escalating broader trade-offs appropriately.
• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.

Preferred Requirements

• Advanced degree in a quantitative discipline.
• Experience deploying or operationalizing predictive or statistical models.
• Background in consumer products, with experience using data to understand user behavior and inform engagement, retention, monetization, or other key customer outcomes.
• Experience building frameworks that improve experimentation velocity and decision quality.
• Familiarity with privacy-preserving data modeling and compliance standards such as GDPR or CCPA.
• Experience mentoring junior data scientists, analysts, or interns.

Pay

The base salary range for this position is $159,945 - $188,171.

Benefits

• Equity: Full-time employees receive equity in Fetch, so everyone can benefit from Fetch’s growth.
• 401k Match: Dollar-for-dollar match up to 4%.
• Health Benefits: Comprehensive medical, dental, and vision plans for employees and their pets.
• Continuing Education: $10,000 per year in education reimbursement.
• Employee Resource Groups: Participate in employee-led groups centered around fostering a diverse and inclusive workplace through events, dialogue, and advocacy.
• Paid Time Off: Flexible PTO, 9 paid holidays, and a year-end week-long break.
• Leave Policies: 20 weeks of paid parental leave for primary caregivers, 14 weeks for secondary caregivers, and a flexible return-to-work schedule.
• Calvin Care Cash: A one-time $2,000 incentive for employees welcoming new family members to assist with childcare, clothing, diapers, and more.
• Flexible Work Environment: Option to work from one of our stunning offices or fully remotely from anywhere in the US, with provided hardware and software.