
501 - 1000 employees
Founded 2013
👥 B2C
📣 Marketing
🔥 Funding within the last year
💰 Later Stage VC on 2026-05
B2C • Marketing
Fetch is a consumer mobile rewards app that lets users scan receipts to earn points that can be redeemed for gift cards and other rewards. The app awards points for everyday purchases (groceries, fuel, meals, games, etc. ), offers in-app games and promotions, and provides a business-facing offering (Fetch for Business) and browser extension. Fetch reports millions of monthly earners, millions of app reviews, and over $1B in rewards redeemed. The service emphasizes easy receipt scanning, point accumulation, and low-effort rewards for shoppers.
🔥 50 minutes ago
🇺🇸 United States – Remote
💵 $159.9k - $188.2k / year
⏰ Full Time
🟠 Senior
📊 Data Scientist
👻 Ghost score 0%
Where this job comes from
Posted on Fetch's careers page, not through a job board
First seen by Remote Rocketship 50 minutes ago

501 - 1000 employees
Founded 2013
👥 B2C
📣 Marketing
🔥 Funding within the last year
💰 Later Stage VC on 2026-05
B2C • Marketing
Fetch is a consumer mobile rewards app that lets users scan receipts to earn points that can be redeemed for gift cards and other rewards. The app awards points for everyday purchases (groceries, fuel, meals, games, etc. ), offers in-app games and promotions, and provides a business-facing offering (Fetch for Business) and browser extension. Fetch reports millions of monthly earners, millions of app reviews, and over $1B in rewards redeemed. The service emphasizes easy receipt scanning, point accumulation, and low-effort rewards for shoppers.
• Independently own a defined audience or measurement product from problem framing through delivery. • Translate advertiser goals and purchase behavior into audience definitions, labels, and predictive models. • Build and validate statistical expansion beyond Fetch users, testing quality, calibration, and reach on held-out populations. • Keep observed purchases distinct from inferred propensity. • Combine receipt, partner, panel, survey, and contextual data into reliable datasets, accounting for linkage uncertainty, missingness, and coverage. • Apply weighting or calibration where warranted. • Design credible studies linking ad exposure to receipt-observed purchases, using experiments when feasible and justified observational methods when necessary. • Check receipt coverage, exposure matching, selection bias, and uncertainty; distinguish attribution from incrementality. • Turn customer problems into scoped products with success criteria and launch recommendations. • Balance audience quality, reach, advertiser value, user value, revenue, and cost. • Feed campaign outcomes back into audiences and models using holdouts and fresh data. • Partner with Sales and GTM to shape pilots and explain product value, methods, and limitations. • Build reproducible datasets, analyses, and validation checks with Product, Engineering, and ML engineers. • Move prototypes into production. • Document methods, share reusable code, and pass knowledge to the team. • Collaborate with Product, Engineering, Sales, and GTM and explain products to customers.
• 5+ years of experience in data science, machine learning, or applied analytics. • Demonstrated ownership of complex analytical problems in product-driven environments. • Experience owning an audience, measurement, or data product from an ambiguous question through delivery and a business decision. • Regular collaboration with product, engineering, and commercial partners; ability to explain customer needs and personal contributions clearly. • Experience building useful datasets from fragmented, incomplete, or biased sources and assessing their validity. • Strong population inference skills, including generalizing from an observed sample to a broader population and checking who is missing. • Experience building propensity or audience models and validating population coverage, calibration, and measured outcomes. • Hands-on causal inference experience, including defensible experiments or observational studies and separating attribution from incrementality. • Strong SQL, Python, applied statistics, and predictive modeling skills. • Habit of building reusable, reproducible assets. • Ability to explain scientific findings clearly to nontechnical and customer audiences. • Sound judgment about when to work independently and when to seek review. • Applied experience in monetization data science, audience development, advertising measurement, market research, or consumer panels is strongly preferred. • Experience with panel, survey, consumer research, or purchase data is preferred. • Background in political science, survey methodology, econometrics, demography, or another quantitative field is preferred.
• Equity: We offer full-time employees equity in Fetch, so that everyone can benefit from Fetch’s growth. • 401(k): Fetch will match your contributions dollar for dollar, up to 4% of your eligible pay. • Comprehensive medical, dental, and vision plans for everyone, including pets. • Ten thousand per year in education reimbursement. • Employee Resource Groups with events, dialogue, and advocacy. • Flexible PTO, 9 paid holidays, and a year-end week-long break. • 14 weeks of fully paid parental leave for all employees, plus 6 additional weeks of paid childbirth recovery leave for birthing parents and a flexible return-to-work schedule. • One-time $2,000 Calvin Care Cash incentive for employees welcoming new family members. • Flexible work environment; fully remote work from anywhere in the US for US-based roles. • Hardware and software provided for remote work.
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