Use exploratory data analysis to uncover hidden patterns in the customer journey
Investigate anomalies in the funnel, identifying whether shifts are driven by market trends, product changes, or technical friction
Analyze weekly performance across the GTM funnel to understand drivers of acquisition and retention
Synthesize complex technical findings into clear, actionable narratives for senior leadership
Contribute to shared code libraries, peer-reviewing complex analyses, and partner with Data Engineering to optimize data architecture for high-velocity analytics

Requirements

5+ years of experience in data science, applied machine learning, or quantitative analysis
Expert-level SQL and Python skills for data manipulation and modeling
Familiarity with big data platforms like Databricks or Spark is highly preferred
Experience with one or more data visualization tools such as Tableau or Power BI
Strong grasp of probability, regression, time-series forecasting, and causal inference
Experience with uplift modeling or survival analysis is a significant plus
A track record of working cross-functionally with non-technical collaborators to drive project roadmaps from ideation to delivery
MS in a quantitative field (Statistics, Computer Science, Economics, Mathematics, or related) or equivalent experience

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data analysisSQLPythondata manipulationdata modelingprobabilityregressiontime-series forecastingcausal inferenceuplift modeling

Soft Skills

communicationcollaborationproblem-solvingnarrative synthesiscross-functional teamworkproject management