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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in product analytics and decision science, with a strong foundation in applied statistics and causal inference methods. Capable of designing and analyzing A/B tests, translating product questions into actionable insights, and effectively communicating findings to senior leadership.
Highest-signal resume keywords
Product AnalyticsA/B Test DesignCausal Inference MethodsAdvanced SQLPython or R
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Quantitative AnalysisStatistical RigorMetric FrameworksForecasting ModelsRoot-Cause InvestigationReproducible WorkflowsBias and Variance DiagnosisExperiment DesignOpportunity SizingData Storytelling
Soft Skills
MentoringClear WritingDirect Storytelling
Tools & Technologies
Experimentation PlatformsMetric StoresMeasurement Tooling
Industry Keywords
Technology CompanyFinancial ServicesInsuranceGrowthPricingMonetizationMarketplaceRecommendation Systems
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Provide quantitative rigor, behavioral insight, and strategic perspective to organizational partners
- Partner with product, engineering, and design leaders to frame business questions and pressure-test roadmap assumptions
- Define goal metrics, guardrails, and supporting metric trees
- Design, power, and analyze A/B and quasi-experiments
- Analyze heterogeneity, long-term impact, novelty effects, and cross-surface interactions
- Apply causal inference methods when randomization is not feasible
- Build opportunity sizing, forecasting, and ROI models
- Lead root-cause investigations into user behavior, funnel performance, retention, and engagement
- Translate product questions into research designs, analyses, and deliverables
- Present findings and recommendations to senior leadership
- Mentor junior data scientists and analysts
- Define standards for experiment design, statistical rigor, and reproducible analysis
Requirements
What you’ll need- 8+ years in product analytics, decision science, data science, or a closely related quantitative role at a technology company
- Track record of influencing product decisions
- Strong background designing well-powered A/B tests
- Experience diagnosing bias and variance issues, handling interference and non-stationarity, and interpreting results under real-world conditions
- Solid applied statistics foundation
- Practical experience selecting appropriate causal inference methods
- Advanced SQL
- Working proficiency in Python or R
- Experience with analysis, modeling, and reproducible workflows
- Ability to define metric frameworks for a product area
- Clear writing and direct storytelling with data
- Ability to produce one-pagers and present to executives
- Bachelor's degree or higher in statistics, economics, computer science, mathematics, operations research, or a related quantitative field—or equivalent practical experience
- Preferred: Bayesian methods, hierarchical models, sequential testing, or uplift modeling
- Preferred: growth, pricing, monetization, marketplace, or recommendation experience
- Preferred: experience working alongside ML engineers on production models
- Preferred: contributions to experimentation platforms, metric stores, or measurement tooling
- Preferred: MS or PhD in a quantitative discipline
- Preferred: insurance or financial services experience
Benefits
Comp & perks- Personalized development programs
- Mentorship
- Certification assistance
- Inclusive and collaborative culture
- Competitive pay
- Benefits
- Flexible work arrangements
- Reasonable accommodations for qualified individuals with disabilities