Lead Data Scientist
At Rockstar Games, we create the games we would want to play ourselves.
A career at Rockstar is about being part of a team working on some of the most creatively rewarding, large-scale projects to be found in any entertainment medium. You would be welcomed to a friendly, inclusive environment where you can learn, and collaborate with some of the most talented people in the industry.
Rockstar New York is on the lookout for a talented Lead Data Scientist who possess a passion for data and games. This candidate loves a variety of data, contexts, business problems, and methodologies; they also want to pick the best solution for the situation. This is a full-time permanent position based out of Rockstar’s unique game development studio in the heart of downtown Manhattan.
What We Do
- The Rockstar Analytics team provide insights and actionable results to a wide variety of stakeholders across the organization in support of their decision making.
- We partner with multiple departments across the company to design and implement data and pipelines.
- We collaborate as a global team to develop cutting-edge data pipelines, data products, data models, reports, analyses, and machine learning applications.
- Lead the development of consumer-ready analysis to analytics team leadership, live producers, product managers, and partner groups.
- Assure Rockstar’s ongoing competitive advantage through best-in-class Machine Learning initiatives that have a high potential of applicability in industry.
- Identify and lead analytic experiments aligned with long-term, strategic initiatives.
- Lead the design, development, and delivery of machine learning enabled solutions to address critical business or game questions.
- Lead the design and development of validation tests to assess the efficiency of the model (or algorithm) in place and provide strategic insights to stakeholders.
- Lead the development of frameworks, models, tools, and processes to ensure data influences decisions at all levels.
- Collaborate with the analytics tech lead to establish best practices for repeated application.
- Lead and inspire a team of world class data scientists, providing leadership through coaching and mentorship on a regular basis.
- Act as an SME for all data availability, quality, and analysis possibilities on all our games.
- Influence the analytics roadmap.
- Participates in the recruitment of the best in class data scientists.
- 3+ years of experience managing/supervising a team.
- 8+ years of experience in data science or similar role in the video game, marketing, finance, forensics, or technology fields required.
- 8+ years of experience in machine learning, statistical languages, and systems such as Python and R.
- Extensive knowledge of machine learning techniques such as k-NN, Naive Bayes, SVM, Decision Forests, Data Mining, Clustering, and Classification.
- Bachelor’s degree in Computer Science or related field, with a strong quantitative background.
- Ability to develop and maintain good relations and communicate with people at all hierarchical levels.
- Strong problem-solving skills.
- Ability to reconcile technical and business perspectives.
- Autonomy and entrepreneurship.
- Strong mentoring abilities.
- Strong team spirit.
- Passion for Rockstar Games and our titles.
Please note that these are desirable skills and are not required to apply for the position.
- Experience with Hadoop.
- Graduate degree (MBA, MSc or Master’s, PHD).
- Game industry experience.
How To Apply
Please apply with a CV and cover-letter demonstrating how you meet the skills above. If we would like to move forward with your application, a Rockstar recruiter will reach out to you to explain next steps and guide you through the process.
Rockstar is proud to be an equal opportunity employer, and we are committed to hiring, promoting, and compensating employees based on their qualifications and demonstrated ability to perform job responsibilities.
If you’ve got the right skills for the job, we want to hear from you. We encourage applications from all suitable candidates regardless of age, disability, gender identity, sexual orientation, religion, belief, or race.