Product Data Scientist (Growth)

OpenArt AI is building data-driven growth for its product, with high autonomy, a high growth environment, and meaningful equity tied to what you ship. This Product Data Scientist role focuses on retention and funnel performance, partnering closely with PMs and engineers to turn behavioral insights and rigorous experimentation into decisions that move key metrics across the user lifecycle.

What you’ll do

• Design, run, and analyze A/B tests and other causal experiments across signup, onboarding, activation, monetization, and retention touchpoints.
• Own experimentation from end to end: set targets for experimental rigor including test sizing, MDE, run duration, primary and secondary metrics, and readout standards.
• Troubleshoot complex experiment issues such as sample ratio mismatch, novelty effects, interaction effects, multiple comparisons, and segment heterogeneity.
• Build and scale an experimentation practice as the company grows, including playbooks, guardrails, and post-launch validation.
• Lead deep-dive growth funnel analyses spanning signup, activation, paid conversion, retention, and “retention resurrection”.
• Drive retention insights by identifying drivers of long-term retention versus churn, then turning findings into product recommendations.
• Use LTV and cohort analysis to inform pricing, packaging, and broader monetization decisions.
• Perform behavioral segmentation to determine which user segments matter and what drives their behavior.
• Quantify opportunity sizing so proposed product changes can be evaluated before engineering builds.
• Define and maintain core product metrics (activation, engagement, retention, monetization) alongside PMs.
• Build and validate dashboards that leaders trust, and keep metric definitions consistent across product, marketing, and finance.
• Translate analyses into clear, opinionated recommendations that PMs, engineers, and executives can act on.
• Push back with data when an experiment is underpowered, mis-scoped, or measuring the wrong outcome.

What you bring

• 3–6 years of experience in data science or analytics supporting product, growth, or lifecycle teams (level and title flexible).
• Solid A/B testing depth.
• Strong SQL and Python, comfortable working end-to-end with data without hand-holding.
• Strong statistical foundation.
• Product intuition and an instinct for turning signals into insights.
• Excellent communication, able to present a clear data story to PMs, engineers, or a CPO and hold your own in discussions.
• High ownership and comfort operating in ambiguity.
• Experience as an early hire at a consumer startup.
• Experience with consumer products, marketplaces, or subscription businesses.
• Experience with experimentation platforms (in-house or vendor such as Statsig or Optimizely).
• Familiarity with causal inference beyond A/B tests, including diff-in-diff, synthetic control, propensity matching, or CUPED.
• Experience with the stack: BigQuery, Amplitude, Metabase, Stripe, GCP.
• Exposure to AI/ML products or generative AI.
• Comfort working across time zones with a globally distributed team.

Tech you’ll use

SQL, Python, BigQuery, Amplitude, Metabase, Stripe, GCP, Statsig, Optimizely

Work setup

• Location: San Carlos, CA (hybrid)
• Visa sponsorship: available
• Remote: considered for exceptional candidates

Compensation & benefits

• Competitive base salary and bonus program
• Equity with meaningful ownership in what you build
• High autonomy and a high growth environment