Staff Data Scientist – Platform

🔥 2 hours ago

🌐 Canada, United States – Remote

🇨🇦 Canada – Remote 🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

📊 Data Scientist

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Fetch Rewards

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2013

💼 Consulting

🍽️ Food & Beverage

📦 Logistics

💰 Debt Financing on 2022-04

Consulting • Food & Beverage • Logistics

Fetch Rewards is a company that operates America's Rewards App, leveraging the power of Fetch Points to drive consumer behavior and engagement across various industries, including Consumer Packaged Goods (CPG), retail, and restaurants. By offering custom-fit marketing solutions, Fetch helps brands increase sales, improve retention, and build lifelong consumer loyalty without relying on discounts. The platform offers dynamic in-app offers based on verified shopping behavior, designed to inspire specific business outcomes and increase customer engagement. Fetch Rewards partners with major brands and retailers, providing a robust data-driven approach to enhance buying frequency and customer retention.

📋 Description

• Define and own Fetch's company-level measurement framework anchored in MAU × ARPU • Establish decision frameworks for pricing, incentives, and value trade-offs • Set standards for evidence quality, uncertainty, and confidence in decision-making • Define the causal reasoning model used across product, growth, marketing, and finance • Own the scientific capability roadmap, including elasticity, value curves, marketing mix modeling, and forecasting • Architect the semantic mart and metric logic powering FetchGPT and scalable insights • Define canonical metric definitions and unify logic across experimentation platforms, dashboards, and diagnostics • Partner with Analytics Engineering and Data Platform to build foundational data assets • Establish BI standards and eliminate redundant or conflicting dashboards • Serve as the quality bar for high-impact analytics and diagnostics • Review strategic analyses for correct interpretation and mechanism alignment • Set scientific rules for experimentation and validate high-risk pricing and incentive tests • Ensure observational and experimental results reconcile cleanly • Create templates and interpretation guides to standardize rigor • Own cross-company models driving executive decisions, including marketing mix modeling, elasticity and incentive sensitivity, value expectation curves, strategic forecasting, and financial mechanism models • Raise the scientific maturity of the data science and analytics organization • Design upskilling programs in statistics, causality, modeling, and storytelling • Author best-practice modeling libraries and documentation • Serve as a technical anchor and thought partner for senior individual contributors • Establish norms for rigorous, transparent, mechanism-driven insights • Apply advanced statistical and causal methods to company-level problems • Build scalable, production-ready analytical frameworks with engineering • Champion experimentation design, model validation, and reproducibility • Leverage Python, SQL, Snowflake, dbt, and experimentation platforms

🎯 Requirements

• 8+ years of experience in data science, economics, statistics, or applied research, including experience operating at Staff or Principal scope on company and/or org-level problems • Deep expertise in causal inference, experimental design, and observational analysis • Demonstrated ownership of high-stakes business decisions informed by causal evidence • Experience defining and owning company-level measurement frameworks, canonical metrics, or strategic models used by senior leadership • Proven ability to influence and support executive decision-making, including presenting trade-offs, uncertainty, and recommendations that directly impact strategy • Exceptional written and verbal communication skills, with the ability to explain complex causal and modeling concepts to non-technical senior audiences • Bachelor's degree in a quantitative field • Advanced degree in a quantitative discipline (preferred) • Hands-on experience owning and maintaining strategic models such as marketing mix models, elasticity estimates, incentive sensitivity, or long-range forecasts used in executive planning (preferred) • Experience in large-scale consumer products, marketplaces, ad-supported platforms, or incentive-driven systems with complex value trade-offs (preferred) • Experience in ads ranking, relevance, retrieval, recommendation, or personalization systems (preferred) • Experience in ad measurement, attribution, incrementality, experimentation, or optimization (preferred) • Core ads product/platform experience (preferred) • Experience defining semantic layers, metric governance, or data contracts at scale across multiple teams or functions (preferred) • Demonstrated track record of org-wide scientific leadership without direct people management (preferred) • Appropriate work authorization for the United States or Canada, as applicable

🏖️ Benefits

• Equity: full-time employees receive equity in Fetch • 401(k): dollar-for-dollar matching up to 4% of eligible pay • Comprehensive medical, dental, and vision plans, including coverage for pets • Continuing education reimbursement of ten thousand per year • Employee Resource Groups and Inclusion Council participation • Flexible PTO • 9 paid holidays for US-based roles; holidays vary for Canada-based roles • 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 • Hardware and software provided for remote work, where applicable

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