Activision Blizzard is looking to build scalable products that empower other data scientists and business analysts within their Global Analytics, Game Studios, Finance, and Marketing organizations. They need to enhance their A/B testing framework, develop a Propensity ML model factory, create new predictive models for financial sales forecasting, and contribute to a Generative AI-powered anomaly detection product.
Requirements
- Interest in implementing prototype-to-production engineering skills in Python, including best practices such as unit testing, source control, proper documentation, library packaging, versioning, testing, containerization, CI/CD, and task scheduling.
- General machine learning expertise, i.e. regression, classification, clustering algorithms
- Professional MLOPs habits around model validation, testing, and tracking.
- Interest in inferential statistics, e.g. statistical power analysis, significance testing, t-tests.
- Engineering experience in at least one cloud platform such as AWS, GCP, or Azure.
- Experience with LLMs and RAG based workflows.
- Experience with time series ML modeling and Generative AI.
Responsibilities
- Building AI, ML, and DS products.
- Contributing reusable code to internal software libraries, following software engineering best practices.
- Researching and implementing novel Data Science and Machine Learning approaches, incorporating these solutions into our codebase and products.
- Translating requirements from cross-disciplinary teams in Game Operations, Marketing, Game Studios, and Business Planning into data solutions.
- Synthesizing disparate data, detecting and working around broken data, and investigating every possibility until you have a thorough solution.
- Enhancing our A/B testing framework with new methodologies for broader data scientist utilization.
- Developing and supporting a Propensity ML model factory, incorporating novel time series models leveraging player data.
Other
- 2+ years professional experience as a Data Scientist.
- Being a tenacious and self-directed problem solver.
- Being team-oriented, and able to build long-lasting and collaborative relationships effectively.
- Respectfully contributing your professional experience in every conversation.
- Adapting quickly, having a high tolerance for ambiguity, and coordinating effectively on a team.
