Data Scientist (Product)

Join our team as a Data Scientist (Product) and work closely with either the iOS or web team from planning through launch. You will define hypotheses, success criteria, core metrics, and measurement approaches while partnering with Engineering and Data Engineering on instrumentation and data quality. You will lead analysis to uncover patterns in product and user behavior, prioritize high-leverage opportunities, recommend actions, and measure realized impact. Additionally, you will design and evaluate A/B tests, create executive-ready visualizations, dashboards, and decision memos, build machine learning and statistical models, and design AI-native tools and systems.

• Collaborer avec les équipes de développement pour définir des hypothèses, des critères de succès et des approches de mesure.
• Diriger l'analyse pour découvrir des modèles dans le comportement des utilisateurs et recommander des actions.
• Concevoir et évaluer des tests A/B et d'autres mesures de produit, en transformant les résultats en décisions.

• Fluency using AI across exploration, analysis, experimentation, and modeling, including providing relevant context, debugging incorrect outputs, and converting repeatable work into reliable workflows
• 3+ years of experience in product analytics or product data science, acting as the analytics voice within a consumer product team
• High proficiency in SQL and either Python or R, including libraries such as pandas, NumPy, SciPy, or Tidyverse, with strong data-model reasoning and the ability to write and understand analytical code
• A bachelor’s degree in a behavioral or quantitative field, or equivalent practical experience, with a strong statistical foundation
• Experience applying statistical analysis, experimental design, causal inference, and machine learning to product problems, with the judgment to choose an appropriately simple method and translate the result into a specific, actionable recommendation
• Strong written and verbal communication skills, including the ability to explain uncertainty and limitations, persuade technical and nontechnical partners, and lead decisions through to action
• Experience with iOS or web analytics, including instrumentation, release measurement, funnels, or experimentation
• Experience with dbt, cloud data warehouses, and large event datasets
• Experience applying product analytics to a consumer creative product
• Experience building reusable AI-powered data science systems, such as agents, orchestration layers, automated analyses, or evaluation and review workflows
• Strong user empathy, curiosity, and excitement about learning in a fast-moving environment
• A proactive, independent working style: you pursue leads, find the people and context you need, operate through ambiguity, and follow work through from recommendation to action