- Define core data science priorities across teams, deciding which questions and investments to pursue or decline
- Help deliver our core company KPI framework, including its driver tree and sensitivity modeling
- Lead reusable, company-wide analytical frameworks and automation
- Establish governed self-service and agentic workflows that reduce bespoke work and improve decision speed while maintaining scientific quality
- Design reusable frameworks with evaluation and evidence traceability
- Set definitions and targets for certified metrics with owners, and resolve conflicting definitions with partners
- Build KPI trees and decompositions that connect product and business drivers to MAU, retention, ARPU, revenue, and margin
- Choose defensible models and quantify the direction, sensitivity, predictive strength, and time horizon of KPI-to-North-Star relationships
- Validate leading indicators out of sample, distinguishing arithmetic identities, predictive associations, and causal effects
- Build scenarios and defensible team targets
- Set measurement standards and defend identification assumptions, guiding decisions when randomization or causal evidence is limited
- Select observational methods when needed, using 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, trade-offs, and when evidence warrants a change
- 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 adopted across teams
- 8+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments
- Ability to explain which questions and investments you prioritized or declined, and how quantified KPI relationships changed planning or investment decisions
- Proven ability to define KPIs and their hierarchy with multiple stakeholders, structure complex spaces into tackle-able plans, and establish trusted metric definitions adopted across Product, Finance, Commercial, and Engineering
- Track record of aligning Finance and Product on targets, trade-offs, and when evidence warrants a change
- Deep expertise building and validating ML models, including regression, causal inference, and graph models, that connect user behavior and business drivers to retention, monetization, or company outcomes
- Skilled at using models for target setting and scenario planning while distinguishing prediction from causal impact
- Demonstrated ability to set measurement standards and defend identification assumptions when randomization or causal evidence is limited, with enough experimentation knowledge to support product data scientists
- Strong skills in SQL, Python, statistics, causal inference, and forecasting
- Track record of shipping reusable dashboards, diagnostic apps, or analytical frameworks with proven accuracy, adoption, and decision impact, and partnering on productionization of robust SQL/Python assets
- History of mentoring scientists and establishing KPI, measurement, or modeling standards that raise quality across teams
- Hands-on experience automating systems with AI, including personally building and shipping agentic automation used in real analytical or business workflows, whether in production or with internal users
- Ability to explain your contribution and how the system retrieves data, uses tools, and completes tasks
- Proven approach to evaluating agentic systems for numerical and analytical accuracy, traceability, failure handling, and adoption, and reusing that approach beyond a single demo or one-off analysis
- Consumer product analytics experience connecting acquisition, activation, engagement, retention, and monetization
- Experience owning KPI frameworks, causal measurement, or business planning across multiple teams
- Experience in centralized or platform data science
- Experience with experimentation platforms
- Experience with governed self-service analytics
- 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.
- Benefits for humans and pets: We offer comprehensive medical, dental, and vision plans for everyone, including your pets.
- Continuing Education: Fetch provides ten thousand per year in education reimbursement.
- Employee Resource Groups: Take part in employee-led groups that are centered around fostering a diverse and inclusive workplace through events, dialogue, and advocacy. The ERGs participate in our Inclusion Council with members of executive leadership.
- Paid Time Off: On top of our flexible PTO, Fetch observes 9 paid holidays, as well as our year-end week-long break. (Holidays will vary for Canada-based roles)
- Robust Leave Policies: 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.
- Calvin Care Cash: Employees who are welcoming new family members will also receive a one-time $2,000 incentive to assist employees with covering the cost of childcare, clothing, diapers, and much more!
- Flexible Work Environment: Collaborate with your team in one of our stunning offices, or you can work fully remotely from anywhere in the US for US-based roles. We’ll ensure you are equally equipped with the hardware and software you need to get your job done in the comfort of your home. (applicable for most roles)
Skills Required
- 8+ years of experience in data science, machine learning, or applied analytics in product-driven environments
- Experience owning complex analytical problems and explaining prioritization or declined investments
- Ability to define KPI hierarchies and establish trusted metric definitions across Product, Finance, Commercial, and Engineering
- Track record aligning Finance and Product on targets, trade-offs, and evidence-based changes
- Deep expertise building and validating regression, causal inference, and graph models
- Experience using models for target setting and scenario planning while distinguishing prediction from causal impact
- Ability to set measurement standards and defend 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
- Experience shipping reusable dashboards, diagnostic applications, or analytical frameworks with demonstrated accuracy, adoption, and decision impact
- Experience partnering on productionization of robust SQL and Python assets
- History of mentoring scientists and establishing KPI, measurement, or modeling standards
- Hands-on experience building and shipping AI-powered agentic automation for analytical or business workflows
- Ability to explain system contributions, data retrieval, tool usage, 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
- Experience owning KPI frameworks, causal measurement, or business planning across multiple teams
- Experience in centralized or platform data science
- Experience with experimentation platforms
- Experience with governed self-service analytics
Fetch Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fetch and has not been reviewed or approved by Fetch.
-
Healthcare Strength — Benefits information points to comprehensive medical, dental, vision, and life insurance coverage. Feedback suggests employees value the strong health offerings alongside mental-health support.
-
Leave & Time Off Breadth — Policies include flexible or unlimited PTO, paid holidays and sick days, bereavement (including pet) and natural-disaster leave. Feedback suggests time-off breadth is a standout element of the package.
-
Wellbeing & Lifestyle Benefits — Wellness programs, 1:1 coaching, Gympass, team workouts, and nutrition counseling are provided. Office and remote perks such as home-office stipends, snacks, and pet-friendly spaces further enhance lifestyle support.
Fetch Insights
What We Do
Through Fetch Points, the platform transforms everyday actions into rewarding moments, with more than $1 billion in Fetch Points awarded to date. Every day, more than 13 million receipts are submitted on Fetch, creating visibility into $212 billion in gross merchandise value and delivering the largest retail-agnostic, SKU-level view of household spending. This unmatched dataset powers Fetch as an outcomes-based advertising platform that acquires and retains lifelong consumers.
Why Work With Us
At Fetch, we back your ambition. You’ll have the scope, trust, and opportunity to turn bold ideas into meaningful impact for millions of people. Our builder-minded, high-agency, low-ego culture gives you room to shape what comes next and grow in ways that last, all while helping people live rewarded.
Gallery







