Staff Data Scientist at 2K (San Francisco, CA)
Who We Are
Founded in 2005, the 2K label includes some of the most talented game development studios in the world today. Firaxis Games, Visual Concepts, Hangar 13, 2K Czech and Cat Daddy Games. Our world-class team of engineers, developers, graphic artists and publishing professionals are stewards of a growing library of critically-acclaimed franchises such as Battleborn, BioShock, Borderlands, The Darkness, Mafia, NBA 2K, Sid Meier’s Civilization, WWE 2K, and XCOM. 2K is headquartered in Novato, California and is a wholly owned label of Take-Two Interactive Software, Inc. (NASDAQ: TTWO).
2K develops and publishes interactive entertainment globally for console systems, handheld gaming systems and personal computers, including smartphones and tablets, which are delivered through physical retail, digital download, online platforms, and cloud streaming services. 2K publishes titles in today’s most popular gaming genres, including shooters, action, role-playing, strategy, sports, casual, and family entertainment.
Our vision at 2K is to create a diverse and inclusion environment to “Come as You are and Feel Equipped to do Your Best Work!” We are dedicated to promoting diversity, multiculturalism, and equality in all that we do. Our communities are focused on increased access and personal growth, and their greatness depends on a diversity of race, gender, sexual orientation, religion, ethnicity, national origin, and perspective. We're an equal opportunity employer, and we're excited to build the future of co-living with the world's most hardworking and passionate people.
What We Need
We are seeking a Staff Data Scientist to join and lead the experimentation and causal inference team dedicated to supporting 2K sports games, including NBA2K, WWE 2K, PGA 2K, Lego drive and more! On this team, you will be the Lead data authority who contributes directly to drive the research direction in developing methods and tools that increase the rigor and efficiency of our experimentation platform and analyses that are constructed using causal inference techniques. You will work closely with studio and product leadership to help them understand the true impact of the decisions and tests.
What You Will Do
- Effectively identify and apply analytics, causal inference, experimentation, and machine learning techniques for given business problems
- Significant experience and excitement with one or more of the following: advanced statistical techniques for A/B testing, methods for experimental design, observational causal inference, or quasi-experimental analysis. Examples include: quantile testing, sequential testing, variance reduction techniques, variance estimation for ratio metrics, multi-level / hierarchical modeling, statistical surrogate modeling, matching methods, regression adjustment, structural equation models, instrumental variables, regression discontinuity design, and graphical approaches to causal inference
- Lead the design, analysis, and interpretation of experiments Proactively perform data exploration on engagement behaviors to discover future opportunities
- Partner/influence directly with and regularly present insights to key strategic business partners (e.g., Growth Strategy, Marketing, Product Development)
- Liaise with partner Data Engineering and QA teams to define and ensure delivery of high-quality data capture (telemetry) and self-serve business intelligence tools.
- Up-level others on the team through mentorship and peer review using your experience and domain expertise.
Who We Believe Will Be An Outstanding Fit
- 8+ years work experience in data science with a Master or PhD degree in Mathematics, Statistics, Economics, Computer Science, Engineering Sciences (or in another quantitative discipline)
- 5+ years of professional experience with data scripting languages (SQL, python, R, etc.)
- In depth understanding and experience using supervised and unsupervised machine learning techniques
- Solid understanding of causal inference methods (such as propensity score matching, synthetic control methods, etc.)
- You are a creative problem solver, a self-starter with the passion and enthusiasm to drive impact and build whatever is necessary.
- You can optimally balance problem-solving from a technical solution standpoint while providing transparency through concise partner communications.
- Experience in applying statistical analysis, machine learning, and experimentation design within a consumer-facing business
- Proficient with the creation of rich data visualizations and visual story-telling, using platforms such as Tableau
- Plus: Experience in building experimentation platforms and causal inference solutions
- Plus: Familiarity with software engineering practice and working with APIs
- Plus: 2+ years of management experience preferred
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
The pay range for this position in California at the start of employment is expected to be between $125,000 and $190,000 per Year. However, base pay offered is based on market location, and may vary further depending on individualized factors for job candidates, such as job-related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include other elements, including a bonus and/or equity awards, in addition to a full range of medical, financial, and/or other benefits. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an 'at-will position' and the company reserves the right to modify base salary (as well as any other discretionary payment or compensation or benefit program) at any time, including for reasons related to individual performance, company or individual department/team performance, and market factors.