Senior Data Scientist II – Core & Agentic Automation

🔥 2 hours ago

🌐 Canada, United States – Remote

🇨🇦 Canada – Remote 🇺🇸 United States – Remote

💵 CA$186.4k - CA$219.3k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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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 core data science priorities across teams and decide which questions and investments to pursue or decline • Help deliver the core company KPI framework, including its driver tree and sensitivity modeling • Lead reusable, company-wide analytical frameworks and automation • Design, build, evaluate, and maintain agentic analytical workflows using certified metrics to investigate KPI changes and generate evidence-backed hypotheses • Implement monitoring, failure handling, and human review where needed • Design reusable frameworks with evaluation and evidence traceability • Set definitions and targets for certified metrics and resolve conflicting definitions with partners • Build KPI trees and decompositions connecting product and business drivers to MAU, retention, ARPU, revenue, and margin • Select defensible models and quantify KPI-to-North-Star relationships • Validate leading indicators out of sample and distinguish arithmetic identities, predictive associations, and causal effects • Build scenarios and defensible team targets • Set measurement standards and defend identification assumptions • Select observational methods and use diagnostics and robustness checks • Measure accuracy, adoption, reduced bespoke analysis, and time to decision • Build reproducible, tested analytical workflows in SQL and Python • Partner with Data Engineering on gold tables and data marts • Shape leadership strategy and team accountability, aligning Finance and Product on targets and trade-offs • Partner with Product, Finance, Commercial, and Engineering to drive adoption • Communicate assumptions and uncertainty clearly • Mentor scientists and establish reusable KPI, measurement, and modeling standards across teams

🎯 Requirements

• 8+ years of experience in data science, machine learning, or applied analytics • Demonstrated ownership of complex analytical problems in product-driven environments • Ability to explain prioritization of questions and investments and their impact on planning or investment decisions • Ability to define KPIs and hierarchies with multiple stakeholders • Ability to structure complex spaces into tackle-able plans • Experience establishing trusted metric definitions across Product, Finance, Commercial, and Engineering • Track record aligning Finance and Product on targets, trade-offs, and evidence-based changes • Experience selecting and validating statistical, predictive, and causal models, including regression, forecasting, sensitivity analysis, and uncertainty estimation • Ability to use models for target setting and scenario planning while distinguishing prediction from causal impact • Experience setting measurement standards and defending identification assumptions when randomization or causal evidence is limited • Experimentation knowledge sufficient to support product data scientists • Strong skills in SQL, Python, statistics, causal inference, and forecasting • Track record shipping reusable dashboards, diagnostic apps, or analytical frameworks with proven accuracy, adoption, and decision impact • Experience partnering on productionization of robust SQL/Python assets • History of mentoring scientists and establishing KPI, measurement, or modeling standards • Hands-on experience automating systems with AI, including personally building and shipping agentic automation used in analytical or business workflows • Ability to explain system contributions, data retrieval, tool use, and task completion • Experience evaluating agentic systems for numerical and analytical accuracy, traceability, failure handling, and adoption • Consumer product analytics experience connecting acquisition, activation, engagement, retention, and monetization (preferred) • Experience owning KPI frameworks, causal measurement, or business planning across multiple teams (preferred) • Experience in centralized or platform data science (preferred) • Experience with governed self-service analytics (preferred) • Appropriate work authorization for the United States or Canada

🏖️ Benefits

• Equity for full-time employees • 401(k) with dollar-for-dollar matching up to 4% of eligible pay • Comprehensive medical, dental, and vision plans, including pets • Ten thousand per year in education reimbursement • Employee Resource Groups and Inclusion Council participation • Flexible PTO • 9 paid holidays (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

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