Staff Data Science Product Manager

sonyinteractiveentertainmentglobal · London

En corto

▸Liderazgo estratégico en productos de análisis, experimentación y modelado de valor del jugador (CLV/LTV).
▸Gestión del ciclo de vida de productos de IA/ML con enfoque en impacto empresarial y escalabilidad.
▸Rol de nivel Staff que impulsa alineación y mejores prácticas en equipos de ciencia de datos a nivel organizacional.

Fluent in English (required)

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

🎧¿Llegás a la entrevista? Llevá el copiloto. Nuestra extensión escucha la entrevista en vivo y te muestra anclas de 3-4 palabras desde tu CV y tu preparación — mirás, conectás, hablás. Gratis. Ver la extensión →

¿Qué piden?

✓Experiencia sólida en product management con enfoque en datos y análisis.
✓Conocimiento profundo en modelos de CLV/LTV y experimentación A/B.
✓Capacidad para liderar problemas ambiguos que requieren coordinación entre equipos.
✓Experiencia trabajando con equipos de ciencia de datos y ML.
✓Habilidades avanzadas de comunicación y influencia sin autoridad.
✓Formación técnica o experiencia equivalente en ciencias de datos, ingeniería o estadística.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

AI/MLAnalyticsExperimentationCLV/LTV modellingData ScienceProduct ManagementCross-functional leadershipTechnical product strategyPlayer value understandingScalable analytics solutions

¿A quién escribirle en sonyinteractiveentertainmentglobal?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

Why Sony Interactive Entertainment? 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. About the Role We are seeking a Staff Product Manager, with a focus in Analytics, Experimentation, and CLV/LTV modelling, to lead the strategy, prioritization, and execution of AI/ML capabilities and products that drive business decision-making. This role operates at the intersection of business, product, data science, and engineering, and is responsible for leading high-impact problem spaces that span teams, while improving the effectiveness, consistency, and scalability of analytics product management practices. This includes technical ML solutions that help the business understand where player value is coming from and how it changes over time. The role is also responsible for creating the conditions for high-performing Data Science and ML teams to deliver quality, production-grade products that drive measurable business value. As a Staff-level individual contributor, this role goes beyond squad ownership to drive alignment across teams, establish best practices, and influence portfolio-level decisions. You will partner closely with Integrated Analytics Partners, Data Science leadership, and Engineering to ensure that analytics investments are coordinated, scalable, and focused on the highest-impact opportunities. This role is critical to enabling a cohesive, product-driven analytics ecosystem, where work is not only delivered effectively within squads but also aligned and leveraged across the organization, including value modelling and player understanding use cases. Key Responsibilities Analytics Product Strategy & Lifecycle Ownership • 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. <s

No apliques sin prepararte

Investigamos quién te entrevista, adaptamos tu CV y te ensayamos en vivo — gratis la primera.