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Staff Data Scientist, Rewarded Apps

🔥 51 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

đź”´ Lead

📊 Data Scientist

Where this job comes from

Posted on Fetch's careers page, not through a job board

First seen by Remote Rocketship 51 minutes ago

Logo of Fetch

Fetch

501 - 1000 employees

Founded 2013

👥 B2C

📣 Marketing

🔥 Funding within the last year

đź’° 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.

đź“‹ Description

• Set the analytical and scientific strategy for Play across revenue, margin, engagement, retention, user experience, and advertiser performance • Serve as a senior thought partner to business, Product, Marketing, and Engineering leaders • Define analytical questions and translate ambiguous business and product challenges into structured analytical approaches • Develop a deep understanding of the Play P&L and connect user behavior and product performance to revenue, margin, and marketplace outcomes • Lead advanced analytics and data science initiatives across engagement, retention, monetization, personalization, segmentation, and marketplace dynamics • Build predictive and machine learning models to identify behavioral patterns, forecast outcomes, prioritize opportunities, and inform strategy • Shape experimentation and measurement strategy using A/B testing, causal inference, quasi-experimental methods, and observational analysis • Develop scalable analytical assets, feature pipelines, modeling frameworks, and trusted measurement systems using Python and SQL • Partner with Product and Engineering to operationalize models, scoring frameworks, and analytical outputs • Translate complex findings into recommendations for senior and executive audiences • Mentor analysts and data scientists, review high-impact analyses, and establish best practices for modeling, experimentation, documentation, reusable code, and data storytelling

🎯 Requirements

• 8+ years of experience in data science, analytics, quantitative strategy, or a related field, including ownership of complex product or business domains • Advanced proficiency in Python and SQL, with experience building reusable analytical and modeling workflows • Experience developing, evaluating, and operationalizing machine learning and predictive models, including feature engineering and translating model outputs into business decisions • Strong foundation in statistics, experimental design, power analysis, metric selection, segmentation, and causal inference • Experience applying causal inference techniques such as difference-in-differences, matching, synthetic controls, or related methodologies • Experience developing models related to personalization, propensity, recommendations, forecasting, retention, or lifetime value • Demonstrated ability to independently structure and solve ambiguous, high-impact problems while balancing analytical rigor with business urgency • Track record of using analytics to drive measurable improvements in revenue, engagement, retention, product performance, or operational efficiency • Proven ability to influence senior stakeholders across Product, Engineering, Marketing, and business teams without direct authority • Experience mentoring analysts or data scientists and improving the quality of work across a broader team • Exceptional communication and data storytelling skills, including explaining sophisticated analytical concepts to non-technical audiences • Preferred: experience in consumer technology, gaming, marketplaces, rewards, loyalty, or another high-frequency digital product • Preferred: experience with dbt, Git/GitHub, Spark, or similar technologies • Preferred: experience with businesses where user engagement, monetization, incentives, and marketplace economics are closely connected • Preferred: experience combining advanced analytics with product and commercial strategy

🏖️ Benefits

• Equity: full-time employees receive equity in Fetch • 401(k) match: dollar-for-dollar matching up to 4% of eligible pay • Comprehensive medical, dental, and vision plans, including pet coverage • $10,000 per year in education reimbursement • Employee Resource Groups and Inclusion Council participation • Flexible PTO • 9 paid holidays • Year-end week-long break • 14 weeks of fully paid parental leave • 6 additional weeks of paid childbirth recovery leave for birthing parents • Flexible return-to-work schedule • One-time $2,000 Calvin Care Cash incentive for employees welcoming new family members • Flexible work environment with remote work from anywhere in the US for US-based roles • Hardware and software provided for home working

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