Manager, Data Science, Payments & Subscriptions

Description

The company behind the PlayStation brand is hiring a Data Science Manager for its Direct to Consumer (D2C) Data Science group, which brings together data science, data engineering and ML engineering to support digital commerce, subscriptions, payments, lifecycle work and player-facing services. The group works with product, engineering, finance, marketing and operations on experimentation, forecasting, modeling and measurement that guides decisions and player experience.

The company is a subsidiary of Sony Group Corporation. It makes PlayStation hardware, runs network services used by more than 100 million people, and owns well-known entertainment intellectual properties.

Location is San Diego, CA. Remote work is considered under flex mode.

This is a hands-on first-line management role focused on how players pay, subscribe and recover from failed payments. You will set the team's science agenda, grow its data scientists, and help partners turn unclear business questions into clear, evidence-based recommendations. You will also review designs, metrics, models and code, help the team weigh uncertainty and tradeoffs, and personally work on some of the hardest problems. Success means a team that can produce rigorous work on its own and improve payment and subscription results.

The starting scope covers payment method performance, payment acceptance, routing and retry logic, subscription recovery, and measurement of experiments and lifecycle changes. Partners need help understanding incremental value, customer friction, processing and operating costs, and risk limits. The scope may widen into neighboring D2C areas as priorities shift.

Responsibilities

• Hire, onboard, lead and develop a team of data scientists covering a defined set of commerce, payments, subscription and lifecycle work.
• Own the team's roadmap, intake, prioritization, capacity planning and stakeholder alignment, and make tradeoffs visible so the team can meet its most important commitments.
• Work with business and technical leaders to set the decisions at stake, hypotheses, success metrics, measurement plans and recommended actions.
• Direct experimentation, causal inference, forecasting and modeling that improve payment and subscription decisions, weighing business value against customer experience, cost and risk limits.
• Review experiment designs, analysis code, data quality, metric definitions, model assumptions, uncertainty and recommendations, and contribute directly to the most complex or high-priority problems.
• Coach data scientists on scientific judgment, influence with stakeholders and communication, delegating work and giving direct feedback with clear expectations.
• Set practical standards for reproducible analysis, documentation, reusable workflows and sharing results. Work with Data Engineering and ML Engineering on data and implementation dependencies.
• Explain recommendations, expected impact, confidence, limitations and next steps so partners can decide and later check outcomes.

Requirements

• At least 6 years of industry experience in data science, applied statistics, machine learning or a related quantitative field, including experimentation, causal inference, measurement or model building.
• At least 2 years of people management, or equivalent formal technical leadership with a solid record of mentoring data scientists or machine learning practitioners and getting results through them.
• Strong grounding in experimentation, causal inference, metric design and decision science for digital products or consumer businesses.
• Deep working knowledge of SQL and Python, enough to review analysis code, challenge assumptions, guide experiment and model design, and contribute to complex analyses.
• A proven record of setting priorities across teams and communicating clear recommendations, confidence levels, tradeoffs and next steps.
• Bachelor's degree or equivalent experience.
• Preferred: experience in digital commerce, payments, subscriptions, billing, lifecycle, gaming, media or large consumer technology businesses.
• Preferred: experience with experimentation platforms, trusted metric frameworks or reusable data science tooling that improves consistency and decision quality.
• Preferred: experience managing senior individual contributors or helping data scientists grow their scope, influence and technical leadership.
• Preferred: familiarity with payment optimization, subscription lifecycle analytics, subscription recovery, payment method selection, pricing or offer measurement, forecasting or customer retention modeling.
• Preferred: experience assessing and improving AI-assisted analytical workflows, including checking outputs and keeping analysis reproducible and data handled appropriately.

Conditions

Base pay is set using market benchmarks and location. The range may vary with the hybrid work policy, and individual pay depends on job-related factors such as knowledge, skills, experience and location.

Estimated base pay range: $186,200 - $279,200 USD.

The role may be eligible for a bonus package.

Background checks are run at the offer stage for all new hires, which may include criminal checks for some roles, and require processing of personal information.

Benefits

• Top-tier benefits package: medical, dental, vision, matching 401(k), paid time off, a wellness program and employee discounts on Sony products.
• The role may also be eligible for the bonus package described above.