Internship Behavioral Data Science Jobs in California

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.
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 PlayStation's 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 PlayStation's 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 role's 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 SIE's 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.
The estimated base pay range for this role is listed below.
$143,400-$215,000 USD
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.
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