Data Scientist II (Hybrid)

Data Scientist

Data Scientist II (Hybrid)

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  • Date posted
    September 30, 2026
  • Expiration date
    December 30, 2026
  • Application ends
    December 30, 2026

We are seeking a highly motivated Contractor Data Scientist to join our Customer Success Data Science team, focused on Smart Expert Growth and Retention. In this role, you’ll be the analytical backbone for understanding how our consumer and expert experiences work together to drive the best possible outcomes for customers – from identifying opportunity, to measuring impact, to uncovering new ways to create value. You’ll partner closely with expert operations, product, and marketing to turn data into decisions, and to prove out where combining human expertise with great customer experience delivers the best results.

Key Tasks:

  • Bring strategic thinking to where and how expert-driven engagement can create the most value for customers – sizing the addressable opportunity, spotting underserved segments, and framing the questions worth answering before jumping to a solution
  • Analyze customer journey and engagement signals to determine the best moments and segments for experts to engage, and build predictive models to flag which customers are most likely to benefit
  • Design and analyze A/B tests, and apply causal methods (propensity matching, diff-in-diff, synthetic control) when clean randomization isn’t feasible, to isolate the true impact of expert engagement on outcomes
  • Partner with expert operations and product to turn data patterns into new ideas, targeting rules, or expert engagement approaches – providing actionable recommendations even when complete data is unavailable

If you’re passionate about using hard data to uncover creative, high-impact solutions at the intersection of customer experience and expert-driven growth, we’d love to hear from you!

Requirements
  • Bachelor’s degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics, or related quantitative field; Master’s preferred
  • 4+ years of experience in product analytics, marketing analytics, or applied data science – ideally with exposure to customer experience measurement, growth analytics, or expert/agent-assisted service models
  • Advanced proficiency in SQL and “big data” technologies (e.g., Databricks, Spark, Redshift, BigQuery); comfort with a BI tool (Tableau, Qlik, Dash)
  • Solid grounding in experimentation design (A/B/n) and causal inference methods (propensity score matching, diff-in-diff, synthetic control) – including comfort applying these when clean experiments aren’t feasible
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