Product Data Scientist (Growth)

OpenArt AI•San Carlos, CA

About The Position

OpenArt is hiring a Product Data Scientist focused on growth and retention to partner with product managers and engineers on data-informed product decisions. The role sits at the intersection of experimentation, product analytics, and growth strategy, with a focus on improving activation, conversion, monetization, and retention through rigorous testing and behavioral analysis. The scientist will design and analyze experiments across signup, onboarding, activation, paywall and pricing, feature adoption, and retention. They will also conduct funnel, cohort, lifetime value, and retention-driver analyses to guide product decisions and quantify the potential impact of proposed changes. The role includes defining product metrics, building and validating dashboards, maintaining consistent metric definitions across teams, and communicating clear recommendations to product, engineering, growth, and executive stakeholders. The position offers high ownership in an early-stage, fast-iteration environment, with the opportunity to build OpenArt’s experimentation infrastructure, growth measurement, and retention frameworks. The Bay Area is preferred, hybrid work is allowed, and remote candidates may be considered. Visa sponsorship is available.

Requirements

3–6 years of experience in data science or analytics supporting product, growth, or lifecycle teams; level and title may vary based on the candidate.
Strong experience designing, running, and analyzing A/B tests.
Strong SQL and Python skills, with the ability to work with data end-to-end independently.
Solid statistical foundation.
Product intuition and strong insight-generation skills.
Excellent communication skills, including the ability to explain data clearly to product managers, engineers, and executives and contribute in discussions with strong opinions.
High ownership and comfort working in ambiguous environments.

Nice To Haves

Experience as an early hire at a consumer startup.
Experience with consumer products, marketplaces, or subscription businesses.
Experience with experimentation platforms, either in-house or vendor tools such as Statsig or Optimizely.
Familiarity with causal inference methods beyond A/B tests, such as difference-in-differences, synthetic control, propensity matching, or CUPED.
Experience with BigQuery, Amplitude, Metabase, Stripe, or GCP.
Exposure to AI/ML products or generative AI.
Comfort working across time zones with a globally distributed team.

Responsibilities

Design, run, and analyze A/B tests and other causal experiments across signup, onboarding, activation, monetization, and retention.
Set standards for experimental rigor, including test sizing, minimum detectable effect, run duration, primary and secondary metrics, and experiment readouts.
Debug experiment issues such as sample ratio mismatch, novelty effects, interaction effects, multiple comparisons, and segment heterogeneity.
Develop OpenArt’s experimentation practice through playbooks, guardrails, and post-launch validation.
Analyze the growth funnel from signup through activation, paid conversion, retention, and resurrection.
Identify drivers of long-term retention and churn and translate findings into product recommendations.
Conduct lifetime value and cohort analyses to inform pricing, packaging, and monetization decisions.
Perform behavioral segmentation to identify important user segments and understand what drives their behavior.
Quantify the potential impact of proposed product changes before engineering builds them.
Define and own key product metrics, including activation, engagement, retention, and monetization, alongside product managers.
Build and validate dashboards that leaders can trust.
Maintain consistent metric definitions across product, marketing, and finance.
Communicate clear, opinionated analytical recommendations to product managers, engineers, and executives.
Challenge experiments that are underpowered, mis-scoped, or measuring the wrong outcomes.