$273,000 – $409,600
Listed on Bend Studio’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Lead the data science product strategy across PlayStation's ecosystem, managing a portfolio of analytics and machine learning products that drive player engagement and business decisions. This role suits experienced product leaders who understand both the technical foundations of data science and how to translate analytical capabilities into measurable business outcomes at scale.
Our summary, not Bend Studio’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- Bachelor's degree in Business, Data Science, Computer Science, Statistics, Economics, Engineering, or related field
- 15+ years of relevant experience
- 8+ years in digital product management, data product management, AI/ML product management, or analytics product management
- 6+ years of people management experience leading Product Managers or senior analytics leaders
- Experience leading complex cross-functional portfolios involving Data Science, ML Engineering, Analytics, Data Engineering, and business stakeholders
- Strong understanding of data science and machine learning workflows including experimentation, predictive modeling, forecasting, segmentation, recommender systems, productionization, and monitoring
- Experience with products or capabilities related to CLV/LTV, personalization, churn, propensity modeling, forecasting, audience targeting, marketing optimization, commerce, or digital engagement
- Ability to translate ambiguous business needs into product strategies, roadmaps, and measurable outcomes
- Strong executive communication skills translating technical concepts to business impact
- Experience leading, mentoring, and developing high-performing product teams
Nice to have
- Experience in gaming, digital commerce, subscription, marketplace, streaming, or consumer technology businesses
- Deep experience with customer intelligence, player lifecycle analytics, personalization, experimentation, audience intelligence, or growth optimization
- Experience defining success metrics and quality standards for data science products including adoption, reliability, latency, interpretability, fairness, and model drift
- Experience building product management capabilities, teams, or operating models from the ground up
- Demonstrated ability to use AI-enabled tools including generative or agentic AI to improve product workflows and decision-making