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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in product data analytics, causal inference methods, and statistical analysis using SQL and Python. Capable of translating complex analytical findings into actionable recommendations while improving statistical literacy across teams.
Highest-signal resume keywords
Causal InferenceA/B TestingSQL Data ModelingPython Statistical AnalysisProduct Data Analytics
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Causal InferenceA/B TestingRegression AnalysisSQLPythonData ModelingStatistical AnalysisExperimental MethodsData AnalysisDecision Science
Soft Skills
AutonomyOwnershipCommunicationProblem-SolvingCollaboration
Tools & Technologies
DatabricksDbtApache AirflowMetabaseSigmaDatabricks GenieElementaryAWS
Industry Keywords
B2B SaaSMarketplace ProductsMedallion Architecture
Tech Stack
Tools & technologiesAirflowApacheAWSPythonSQL
About the role
Key responsibilities & impact- Serve as bsport’s first Product Analyst with an analytics engineering mindset
- Build analysis-specific datasets on top of certified models
- Size opportunities and estimate potential impact of roadmap bets
- Partner with product and engineering to make launches measurable through progressive rollouts, exposure tracking and predefined success metrics
- Own analyses from planning through execution, including eligibility, exposure and outcomes tables
- Measure the impact of product features on studio retention, revenue and activation
- Select appropriate experimental or observational methods
- Investigate unexpected movements in key metrics, identify root causes and recommend actions
- Translate analytical findings into recommendations, decision tools and guardrails
- Improve statistical literacy across the company and communicate when data cannot answer a question
- Agree with product leads on key decisions to measure and conduct analyses
- Develop measurement plans for product launches
- Produce measured outcomes for key annual initiatives to inform future planning
Requirements
What you’ll need- 4+ years in decision science, product data analytics or a similar role
- Hands-on experience with causal inference in a business setting, including A/B tests, geo experiments, difference-in-differences and regression analysis
- Production-grade SQL and solid data modeling experience
- Fluency in Python for statistical analysis
- Experience delivering analyses that changed real decisions
- Ability to choose the simplest method that is good enough
- Ability to explain uncertainty in plain language and turn a confidence interval into a recommendation
- Autonomy and ownership
- Bonus: experience in B2B SaaS or marketplace products
- Bonus: experience with Databricks and dbt
- Knowledge of SQL, Python, Databricks, Apache Airflow, dbt Core, medallion architecture, dbt tests, Elementary, Metabase, Sigma, Databricks Genie, internal AI data agents and AWS
Benefits
Comp & perks- Competitive salary packages based on your experience and role
- Hybrid model with 3 days per week in the office
- Up to 15 days of remote work from abroad each year
- Specially discounted HelloCSE membership
- Multicultural colleagues, after-work events, team-building and more