Data Scientist, D2C Data Science

Why Sony Interactive Entertainment?

Sony Interactive Entertainment isnt just the Best Place to Play its also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, were 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.

Data Scientist, D2C Data Science

San Diego, CA (Hybrd)

About the Team

The Direct to Consumer (D2C) Data Science organization brings together Data Science, Data Engineering, and ML Engineering to support PlayStations digital business across commerce, payments, subscriptions, lifecycle experiences, and player-facing services. We partner closely with product, engineering, finance, marketing, operations, and data teams to turn experimentation, forecasting, modeling, and production-quality measurement into better decisions and better player experiences.

About The Role

We are looking for a Data Scientist to join a focused team within D2C Data Science supporting payment and subscription experiences across PlayStations direct-to-consumer business. This is a hands-on role for someone who can use statistics, machine learning, experimentation, and strong data judgment to help teams make better decisions about how players pay, subscribe, and move through global payment flows.

The initial portfolio is expected to focus on payment method performance, payment flow optimization, subscription payment recovery, and ROI-based evaluation of experiments and business interventions. You will help teams understand customer behavior, payment success, cost and routing tradeoffs, and the business impact of new payment capabilities.

Our team values practical scientific rigor: clear decision framing, trusted reusable metrics, transparent uncertainty, and recommendations that help teams move faster without sacrificing measurement quality. This role is best suited for someone who can independently own well-scoped analyses and models, work through ambiguity, and translate complex data into recommendations that improve customer experience and business performance.

Responsibilities

• Apply data science methods to high-impact questions across D2C payments, subscriptions, commerce, lifecycle, and player experience.
• Design, analyze, and interpret A/B tests, holdouts, quasi-experimental analyses, and other measurement approaches with clear hypotheses, metrics, and decision criteria.
• Analyze payment and subscription outcomes such as payment success, authorization performance, payment funnel behavior, routing or retry performance, cost tradeoffs, and subscription recovery.
• Build statistical and machine learning models for forecasting, segmentation, propensity, retention, payment success, payment optimization, subscription outcomes, or offer performance.
• Use SQL and Python to prepare data, validate assumptions, analyze behavior, and produce reproducible analytical workflows.
• Partner with product, engineering, finance, marketing, operations, and data engineering teams to ensure analyses are technically sound, actionable, and operationally useful.
• Communicate findings with clear recommendations, confidence levels, caveats, tradeoffs, next steps, and reusable documentation that supports better decision-making.

Basic Qualifications

• 3+ years of professional experience in data science or machine learning
• Bachelor's degree in statistics, mathematics, computer science, engineering, data science, or a related quantitative field or equivalent
• Strong SQL and Python skills for data extraction, data validation, analysis, modeling, and reproducible workflows.
• Solid foundation in statistics, experimental design, machine learning, predictive modeling.
• Experience applying data science methods to ambiguous commercial, customer, payment, subscription, or operational problems.
• Ability to communicate technical findings clearly to technical and non-technical partners.

Preferred Qualifications

• Experience with digital commerce, payments, billing, subscriptions, fintech, marketplaces, gaming, media, or scaled consumer technology businesses.
• Experience with payment method performance, authorization or success-rate analysis, payment optimization, routing or retry strategies, cost analysis, payment telemetry, or subscription recovery.
• Experience designing, running, or analyzing experiments, including A/B tests, holdouts, quasi-experimental approaches, or causal inference methods.
• Experience with forecasting, customer segmentation, churn / retention modeling, offer measurement, payment success modeling, subscription lifecycle analytics, or ROI-based business evaluation.
• Experience working with large-scale data environments such as Snowflake, Databricks, Spark, BigQuery , or similar platforms, and familiarity with metric layers or source-of-truth datasets.

At SIE, we consider several factors when setting each roles base pay range, including the competitive benchmarking data for the market and geographic location.

Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.

In addition, this role is eligible for SIEs top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more.

Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.

Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.

Equal Opportunity Statement:

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.