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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data science and product analytics, with a strong foundation in applied statistics and experience in building data solutions. Proficient in using analytical tools and modern AI technologies to drive business decisions and enhance user engagement.
Highest-signal resume keywords
Data Science ExperienceProduct AnalyticsSQL ProficiencyApplied StatisticsAI Fluency
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingReportingHypothesis TestingCausal InferenceConfidence IntervalsPower AnalysisData Solutions DevelopmentExperimentationBusiness Metrics DefinitionData Visualization
Soft Skills
Proactive CommunicationAbility to Convey Statistical Concepts
Tools & Technologies
SQLPythonModern Analytics ToolsExperimentation ToolsLLMsDecision-Support Workflows
Industry Keywords
Consumer Focused ProductsPerformance Marketing OptimizationQuantitative Discipline
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Shape how the Places app uses data to drive business decisions.
- Combine data modeling and reporting with product analysis and experimentation.
- Identify opportunities to improve retention and help the team evaluate and act on them.
- Build data solutions from the ground up and help shape how the team uses insights.
- Articulate best practices and develop analytical frameworks tying user actions to outcomes.
- Own the definition and evolution of success metrics for all user-facing surfaces, balancing short-term and long-term member value.
- Define and maintain business metrics, semantic layers, and data models.
- Partner with Data Engineering to translate product requirements into scalable, reliable data assets.
- Uncover insights and translate them into recommendations shaping roadmap prioritization.
- Build a culture of high-fidelity experimentation.
- Use visualizations to convey nuance clearly.
- Use LLMs, agents, and modern AI tools to automate analysis, accelerate experimentation, and build decision-support workflows.
Requirements
What you’ll need- 5+ years of data science and product analytics experience
- BS and/or MS in a quantitative discipline: statistics, operations research, computer science, engineering, applied mathematics, physics, economics, etc.
- Familiarity in delivering data products through partnership with Data and product engineering teams.
- Strong technical fluency with analytical tools such as SQL and Python, or equivalent experience using data to answer open-ended business questions.
- Strong applied statistics background, including hypothesis testing, confidence intervals, power analysis, and causal inference techniques.
- Familiarity with modern analytics and experimentation tools
- Familiarity with consumer focused products
- Strong in proactive verbal and written communication, ability to convey rigorous statistical concepts to non-experts.
- Practical AI fluency and curiosity about how modern AI tools can improve analytical workflows, strategic synthesis, and decision support.
- Bonus points for familiarity with optimization of performance marketing efforts