Data Scientist

Job Description

The Marketing Data Scientist will develop and operationalize marketing machine learning (ML) models as part of our business planning initiatives, which include optimizing advertising spend and personalizing the player experience. You will be responsible for:
• Design causal ML uplift models to optimize marketing campaigns.
• Build marketing machine learning models (LTV, churn, behavioral segmentation) to drive monetization and engagement.
• Design A/B tests to measure incremental revenue in marketing campaigns.
• Interacting with cross-disciplinary teams in Marketing, CRM, Game Studios and Business Planning to tackle their hardest problems.
• Researching and implementing novel ML approaches for new problems.
• Synthesizing disparate data, detecting, and working around broken data, and investigating every possibility until you have a thorough solution.
• Surfacing and communicating results to technical and non-technical colleagues by generating dashboards and reports.

As a machine learning expert on the team, you will leverage your experience to steer data-driven discussions, improve internal processes, and communicate results to technical and non-technical colleagues. You will be a trusted member of an established team of data scientists and machine learning engineers, focused on ensuring player satisfaction in our games. You will accomplish this by:
• Being a tenacious and self-catalyzing problem solver.
• Driving towards visibility, accountability, and communication.
• Being team-oriented, and able to build long-lasting and collaborative relationships effectively.
• Respectfully contributing your professional experience in every conversation.
• Listening with openness to others.
• Adapting quickly, having a high tolerance for ambiguity, and coordinating effectively on a team.

Player Profile

Minimum Requirements:
• Experience in Marketing/Advertising industry.
• M.S. in Mathematics, Machine Learning, Data Science, Statistics, Operations Research, Economics, or other quantitative field.
• 2+ years experience as a data scientist. Senior level depends on additional experience.
• Solid understanding of statistics, e.g. design of experiments, A/B testing, statistical power analysis, significance testing, t-tests, ANOVA.
• General machine learning expertise, i.e. regression, classification, and clustering algorithms, time-series analysis, Bayesian methods, and survival analysis.
• Advanced SQL and Spark skills.
• Professional habits around model validation, testing, and tracking.
• Engineering experience in at least one cloud platform such as AWS, GCP, or Azure.

Bonus Points:
• Experience with causal ML or uplift modeling.
• Ph.D. with peer-reviewed publications and a proven track record of self-guided research.
• Prototype-to-production engineering skills in Python, including best practices such as source control, proper documentation, library packaging, versioning, testing, containerization, CI/CD, and task scheduling.
• Video game enthusiasm with a solid understanding of the gameplay mechanics in Call of Duty and Warzone.

Jobcode: Reference SBJ-r1ze3v-3-142-171-180-42 in your application.