Note: The job is a remote job and is open to candidates in USA. Fetch is hiring a Senior Data Scientist II to establish trusted company-wide KPI frameworks, measurement standards, and analytical automation. The role leads reusable data science systems and governed self-service and agentic workflows, aligns Finance and Product on targets and trade-offs, and mentors scientists across teams.
Responsibilities
- 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
Skills
- 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
Benefits
- Full-time employees receive equity in Fetch.
- Fetch matches 401(k) contributions dollar for dollar, up to 4% of eligible pay.
- Comprehensive medical, dental, and vision plans for everyone, including pets.
- Ten thousand per year in education reimbursement.
- Employee-led Employee Resource Groups centered around fostering a diverse and inclusive workplace through events, dialogue, and advocacy; ERGs participate in the Inclusion Council with executive leadership.
- Flexible PTO, 9 paid holidays, and a year-end week-long break. Holidays vary for Canada-based roles.
- 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.
- Employees welcoming new family members receive a one-time $2,000 incentive to assist with costs such as childcare, clothing, and diapers.
- Flexible work environment: collaborate from an office or work fully remotely from anywhere in the US for US-based roles (applicable for most roles); hardware and software are provided for working from home.
- Benefits for Canada-based employees may differ slightly to comply with applicable laws, including paid time off and holidays.
Company Overview
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