Lead Product Data Scientist

📋 Description

• • Serve as the primary analytical leader for the Zable app, used by over 1 million customers on iOS and Android, driving product analytics that directly influence user experience and business strategy.
• • Develop, maintain, and evolve key product metrics, dashboards, and reporting frameworks to monitor user behavior, app health, and business performance across the Zable platform.
• • Conduct deep-dive analyses into user segmentation, lifecycle patterns, and engagement drivers to uncover growth opportunities and friction points in the customer journey.
• • Build and deploy predictive models using machine learning techniques to forecast user churn risk, uplift potential, and behavioral trends that inform proactive product decisions.
• • Own the end-to-end A/B testing lifecycle, including experimental design, sample size calculation, execution, statistical analysis, and recommendation delivery to product and engineering teams.
• • Establish and enforce experimentation standards across the team, ensuring statistical rigor, proper hypothesis formulation, and accurate interpretation of test results.
• • Partner closely with Product, Growth, and Engineering leadership to embed data-driven decision-making into daily workflows and translate complex analytical findings into clear, actionable business recommendations.
• • Challenge assumptions and provide data-backed perspectives that shape roadmap prioritization, feature development, and strategic direction for the Zable app.
• • Define and champion analytical best practices, methodologies, and standards within the growth analytics team to ensure consistency, scalability, and reliability of insights.
• • Collaborate with cross-functional stakeholders to identify ambiguous problems, structure them into testable hypotheses, and deliver data-driven solutions with measurable impact.
• • Communicate complex analytical results effectively to non-technical audiences, ensuring alignment across product, engineering, and business teams on key insights and priorities.
• • Build and maintain robust data models and pipelines using dbt, ensuring high-quality, scalable data infrastructure to support product analytics.
• • Apply advanced statistical methods including causal inference, regression analysis, and hypothesis testing to derive reliable insights from observational and experimental data.
• • Act as a strategic thought partner to product leaders by anticipating data needs and proactively identifying areas where analytics can accelerate product evolution and user satisfaction.
• • Translate business objectives into analytical initiatives, ensuring alignment between product goals and the data work being executed.
• • Maintain a deep understanding of user behavior across the Zable app’s entire funnel, from acquisition to retention, and use this insight to drive product improvements and reduce friction.