Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this Manager, Data Science, Payments & Subscriptions role.

Rezi rewrites your resume against PlayStation Global's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the Manager, Data Science, Payments & Subscriptions posting at PlayStation Global — free, in seconds.

About the Role

We are looking for a Data Science Manager to lead a focused team improving how players pay, subscribe, and recover from payment failures. You will own the team’s scientific roadmap, develop data scientists, and partner with product, engineering, finance, marketing, and operations to turn ambiguous business questions into clear recommendations supported by trustworthy evidence. This is a technically engaged first-line management role. You will review experiment designs, metrics, models, analytical code, and recommendations; help the team reason through uncertainty and business tradeoffs; and contribute directly to selected complex problems. Success means building a team that can independently deliver rigorous work, guide decisions, and improve payment and subscription outcomes.

Responsibilities

Lead, hire, onboard, and develop a team of data scientists supporting a defined commerce, payments, subscriptions, and lifecycle portfolio.
Own the team’s roadmap, intake, prioritization, capacity planning, and stakeholder alignment.
Partner with business and technical leaders to define the decisions to be made, hypotheses, success metrics, measurement plans, and recommendations for action.
Guide experimentation, causal inference, forecasting, and modeling work that improves payment and subscription decisions.
Evaluate business value alongside customer experience, costs, and risk guardrails.
Review experiment designs, analytical code, data quality, metric definitions, model assumptions, uncertainty, and recommendations.
Contribute directly to selected high-priority or technically complex problems.
Coach data scientists to strengthen scientific judgment, stakeholder influence, and communication.
Build independent ownership through delegation, constructive review, and clear expectations.
Set practical standards for reproducible analysis, documentation, reusable workflows, and communication of results.
Partner with Data Engineering and ML Engineering to address data and implementation dependencies.
Communicate recommendations, expected impact, confidence, limitations, and next actions so partners can make informed decisions and evaluate outcomes.

Requirements

6+ years of industry experience in data science, applied statistics, machine learning, or a related quantitative field, including work in experimentation, causal inference, measurement, or model development.
2+ years of people management experience, or equivalent experience in formal technical leadership with a strong track record of mentoring, coaching, and driving outcomes through other data scientists or machine learning practitioners.
Strong background in experimentation, causal inference, metric design, and decision science for digital products or consumer businesses.
Deep fluency with SQL and Python, with the technical depth to review analytical code, challenge assumptions, guide experiment and model design, and contribute directly to complex analyses.
Proven ability to prioritize cross-functional work and communicate clear recommendations, confidence levels, tradeoffs, and next actions.
Bachelor's degree or equivalent
Experience in digital commerce, payments, subscriptions, billing, lifecycle, gaming, media, or scaled consumer technology businesses.
Experience with experimentation platforms, trusted metric frameworks, or reusable data science tooling that improves consistency and decision quality.
Experience managing senior individual contributors or helping data scientists expand scope, influence, and technical leadership.
Familiarity with payment optimization, subscription lifecycle analytics, subscription recovery, payment method selection, pricing or offer measurement, forecasting, or customer retention modeling.
Experience evaluating and improving AI-assisted analytical workflows, including validating outputs and preserving reproducibility and appropriate data handling.

Skills

Data Science
Applied Statistics
Machine Learning
Experimentation
Causal Inference
Measurement
Model Development
SQL
Python

Location

San Diego, CA

Work Type

remote considered
flex mode

Experience Level

6+ years of industry experience
2+ years of people management experience

Education Level

Bachelor's degree or equivalent

Salary/Compensations

$186,200—$279,200 USD

Benefits

medical
dental
vision
matching 401(k)
paid time off
wellness program
employee discounts for Sony products
bonus package

About the Company

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 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.

Equal Opportunity

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.