Senior Data Scientist I, Core

About the Role:

What You'll Do at Fetch:

• Independently own a company wide KPI, modeling, or measurement workstream through delivery and adoption
• Contribute to our core company KPI framework, including its driver tree and sensitivity model
• Contribute analysis to planning and points allocation
• Define certified metrics and resolve conflicting definitions with partners
• Build KPI trees and decompositions that connect product and business drivers to MAU, retention, ARPU, revenue, and margin
• Model KPI drivers and quantify the direction, sensitivity, predictive strength, and time horizon of KPI-to-North-Star relationships
• Distinguish arithmetic identities, predictive associations, and causal effects
• Build scenarios and translate company goals into workstream targets
• Apply established observational causal methods with diagnostics and robustness checks, making identification assumptions explicit
• Build reproducible diagnostics and analytical tools grounded in certified data
• Evaluate the accuracy, adoption, and sustained value of what you build
• Build reproducible, tested analytical workflows in SQL and Python
• Partner with Data Engineering on gold tables, data marts, and semantic layers
• Partner with cross-functionally with teams such as Product and Engineering to drive adoption
• Make actionable recommendations and communicate sensitivity, assumptions, and uncertainty clearly

Minimum Qualifications:

• 5+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments
• Experience working with multiple stakeholders to define KPIs and their hierarchy
• Ability to structure a complex space into a tackle-able project plan
• Track record of establishing trusted metric definitions and driving adoption across Product, Finance, Commercial, and Engineering
• Experience building and validating models that connect user behavior and business drivers to retention, monetization, or company outcomes
• Ability to show sensitivity estimates, leading indicators, time horizons, and out-of-sample predictive performance
• Experience using models in target setting or scenario planning while distinguishing prediction from causal impact
• Experience with ML modeling, including regression, causal inference methodology, and graph models
• Experience modeling multi-metric relationships
• Strong skills in SQL, Python, statistics, causal inference, and forecasting
• Track record of shipping reusable dashboards, diagnostic apps, or analytical frameworks with evidence of accuracy, adoption, and decision impact
• Experience building robust SQL/Python analytical assets and partnering on productionization
• Track record of documenting and sharing reusable methods
• Understanding of experimentation methodology sufficient to identify patterns, concerns, and frameworks that support product data scientists

Preferred Qualifications:

• Consumer product analytics experience connecting acquisition, activation, engagement, retention, and monetization
• Experience owning KPI frameworks, causal measurement, or business planning
• Experience in centralized or platform data science
• Experience with experimentation platforms
• Experience with governed self-service analytics

• Reviewing and organizing applications and resumes to help our recruiting team manage high volumes of submissions, including automated review of fraud signals to identify bad actors;
• Identifying candidates whose stated qualifications and experience appear relevant to an open position;
• Scheduling and coordinating interviews with candidates;
• Generating interview summaries or notes to assist recruiters and hiring managers in their review; and
• Conducting research on open roles and candidate pools to improve the effectiveness of our recruiting practices.