Data Science Product Manager

Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.

• Lead discovery and definition of ambiguous, high-impact AI/ML problem spaces that require coordination across teams, including applications that improve understanding of player value and value drivers. 

• Drive alignment across squads to ensure coordinated execution and avoid duplication of effort. 

• Identify opportunities to scale solutions, reuse components, and standardize approaches across analytics, experimentation, forecasting, and value modelling use cases. 

• Lead product thinking across the end-to-end ML lifecycle, from opportunity framing and evaluation design through deployment, monitoring, iteration, and long-term value realization. 

• Own prioritization across multiple squads, balancing business impact, feasibility, technical maturity, adoption potential, and resource constraints. 

• Partner with Integrated Analytics Partners and senior Data Science and Product leaders to align work to business strategy. 

• Help shape how analytics work is sequenced and balanced across new feature development, operationalization, and productization, including roadmaps for technical ML teams. 

• Partner with Data Science leaders to ensure statistical rigor and methodological consistency across experimentation, modelling, forecasting, and player value analysis. 

• Drive adoption of experimentation and value-based analytical techniques as core decision-making tools across business functions. 

• Partner closely with other Product Management teams and cross-functional leaders to operate as a unified team to deliver cohesive strategies and stakeholder communication. 

• Align Analytics strategy, prioritization, and execution through collaboration with the Integrated Analytics Partners, Data Science leadership, and Engineering leadership. 

• Coordinate work across multiple squads to deliver integrated analytics solutions. 

• Influence stakeholders across functions to drive alignment and execution. 

• Drive thinking around scalability, reuse, and long-term sustainability of analytics solutions, particularly where shared capabilities can improve understanding of player value. 

• Partner with AI/ML Engineering to transition high ROI, high SLA capabilities into scalable, production-grade systems. 

• Define success criteria for analytics and ML products, including business impact, adoption, reliability, interpretability, and operational sustainability. 

• Ensure successful adoption of AI/ML capabilities by end users. 

• Ensure analytics and ML capabilities are embedded into business workflows and decision-making processes so that technical outputs translate into durable operational impact. 

• Advocate for investments in shared capabilities and platforms when beneficial. 

• Engage with business stakeholders to understand needs, gather feedback, communicate progress, and clarify how analytics and ML outputs inform player value understanding. 

• Support Integrated Analytics Partners in translating strategic priorities into actionable work. 

• Communicate outcomes and impact of analytics initiatives clearly and effectively, including how they support business understanding of value, growth, and customer lifecycle dynamics. 

• Define and promote best practices for analytics product management, including prioritization, experimentation, and lifecycle management. 

• Mentor and support other Analytics Experimentation & Product Leads. 

• Identify gaps in how work progresses through the lifecycle and drive improvements. 

• Raise the overall quality and consistency of work across teams. 

• Create the conditions for high-performing Data Science and ML teams by clarifying priorities, reducing delivery friction, and strengthening cross-functional ways of working across discovery, development, deployment, and adoption. 

Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.

We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. 

Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.