Senior Data Scientist

Job description

At 2K, we create some of the most iconic and culture-shaping video games in entertainment, including ***NBA® 2K***, one of the top-selling franchises in the world, and legendary titles like ***BioShock®****,* ***Borderlands®****,* ***Mafia****,* ***Sid Meier’s Civilization*****®**, and***XCOM®***, as well as fan favorites ***WWE® 2K****,* ***TopSpin®***, and ***PGA TOUR® 2K****.* We build unforgettable experiences by pushing the boundaries of creativity, authenticity and innovation across every genre. Our portfolio is brought to life by some of the most influential game development studios in the world. **Visual Concepts, Firaxis Games, Hangar 13, Cat Daddy Games, 31st Union, Cloud Chamber, Gearbox, HB Studios,** and **2K SportsLab** create world-class experiences across platforms. But what truly powers 2K is our people. We believe the best ideas come from teams that feel empowered, supported, and inspired. As an equal opportunity employer, we are committed to fostering a diverse, inclusive workplace where people are encouraged to **come as they are** and do their best work. **What We Need** The Senior Data Scientist (P5) is a senior individual contributor who turns ambiguous business problems from marketing, product, and commercial teams into models and experiments the business can trust and act on. The role owns the data science systems behind that work — keeping models reliable in production and experiments methodologically sound — and serves as the technical lead on the highest-stakes projects. The Senior Data Scientist works with significant independence while partnering closely with senior stakeholders. **What You’ll Do** - Technical Architecture & System Ownership: Own the design, reliability, and long-term availability of end-to-end Data Science systems, accounting for performance and technical bottlenecks in production-grade predictive models and AI solutions. - Experimental Frameworks: Architect rigorous experimental systems across cross-functional teams, ensuring validation methods are standardized, repeatable, and scalable. - Business Insight & Problem Definition: Partner closely with marketing, product, and commercial teams to diagnose business challenges — spanning areas such as gamer engagement, marketing efficiency measurement, and regional strategy — and define appropriate metrics, analyses, and interpretations to drive strategic decisions. - Statistical & Predictive Modeling: Define requirements for and lead the creation, monitoring, and iterative improvement of key statistical models and AI solutions used for marketing spend optimization, product growth, and player engagement. - Executive Communication & Narrative: Design clear, unambiguous narratives and visualizations to communicate complex data initiatives to broad, non-technical audiences up to the executive level. - Collaboration & Cross-Functional Partnership: Work closely with peers across the broader data and analytics organization toward shared goals — aligning on data sources, standards, and priorities early, and sharing knowledge so the whole team's work compounds rather than duplicates. - Technical Consultation: Reason effectively about the strengths and weaknesses of different modeling approaches, selecting and iterating on combinations that suit specific business contexts. **Core Competencies** - Behavioral: Solution-oriented, creative problem solver, and self-starter; proactively identifies potential issues; builds compelling narratives from raw data; collaborative and genuinely invested in the work of cross-functional partners. - Functional / Technical: Advanced R or Python programming ability for sophisticated multi-dimensional data sets; advanced SQL “data carpentry” skills across modern data warehouse environments; able to independently implement advanced predictive models. - Strategic Influence: Strong understanding of the business and the context surrounding business asks; ability to bridge technical and business needs and influence product, marketing, and commercial strategy through data-backed evidence at all levels of the organization. **Required Qualifications, Knowledge, and Job-Related Skills** - Education: BSc, MSc, or PhD in Mathematics, Statistics, Economics, Computer Science, Data Science, Engineering, or another quantitative field. - Experience: 3–5 years of professional experience in data science or machine learning, building models with complex datasets, with a consistent track record of business impact. - Data Systems: Proven experience in relational databases and SQL; ability to work independently within a data warehouse environment. - Methodological Depth: Cognizant of the pros and cons of common methodologies; demonstrated ability to apply various modeling approaches and iterate based on performance. - Communication: Excellent verbal and written communication skills with a track record of cross-functional collaboration and presenting to senior stakeholders. **What Will Make You A Great Fit** - Experience in the game-related tech industry (e.g., FAANG, other game companies, etc.). - Experience with Bayesian modeling and causal inference tools such as RStan and CausalImpact, or their Python equivalents. This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Other tasks and duties may be assigned or reassigned as needed. Please note that 2K Games and its studios never uses instant messaging apps or personal email accounts to contact prospective employees or conduct interviews and when emailing, only use <2K.com> accounts.