Drimva

Intuit

Senior Staff Data Scientist - Credit Karma Engagement

$210K–$284K

Oakland, California +1 · Senior Staff · Full-time · Posted Sep 15, 2026

Location
Oakland, California
Charlotte, North Carolina
Experience
9+ years in data science and analytics.
Education
BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field (advanced degree preferred).

About the job

Leads data science strategy for Credit Karma engagement and lifecycle products, using experimentation, causal inference, segmentation, and AI to improve member retention and financial outcomes.

What you'll do

  • Set analytics strategy across activation, engagement, retention, churn prevention, and reactivation initiatives; influence cross-functional leaders.
  • Design complex experiments and apply causal inference; develop reusable methods and member segmentation strategies.
  • Shape the AI roadmap, establish measurement and safety practices, and mentor data scientists while contributing hands-on.

What they ask for

  • 9+ years of experience in data science and analytics, driving strategy and impact across multiple initiatives or business units.
  • Deep expertise in causal inference, customer segmentation, and experimentation design.
  • Experience designing and interpreting complex experiments and applying causal inference when experimentation is constrained.
  • BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field.

Nice to have

  • Consumer product engagement, retention, or growth experience; fintech experience is a plus.
  • Experience in membership-based or multi-product consumer platforms; advanced degree preferred.

Pay

Oakland $210,500 - $284,500 (base salary)

Tools

A/B/n, painted-door, bandits, Propensity Score, DiD, Synthetic Control, Machine Learning

AI focus

Co-create the analytics/AI strategy for engagement and lifecycle, guide phased testing and rollout with measurement, safety, risk, and ethical considerations, and use AI-native tools to plan, implement, and synthesize analyses.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 6, 2026 (UTC)