Senior Machine Learning Data Scientist

Bungie•United States, Remote, WA

8h•$165,000 - $185,000•Hybrid

About The Position

Bungie is seeking a Senior Data Scientist to join our Product Security Team. In this role, you will directly support Bungie’s product security initiatives, working closely with analysts and engineers to reduce the impact of bad actors in Bungie games. At Bungie, we build worlds that inspire friendships. Protecting players in a rapidly changing threat landscape requires machine learning automation, data driven discovery, and careful analysis of a dynamic online global ecosystem. You will leverage your experience in data analysis, data science, and engineering to build security services that protect Bungie players and track emerging threats. Most importantly, your work will be essential to developing unmatched entertainment experiences that inspire friendships and lifelong memories.

Requirements

Ability to utilize cloud-based infrastructure to design, deploy, and manage models while using SQL at scale within a live service environment.
Expertise in developing, evaluating, applying, and deploying advanced machine learning algorithms and statistical models, including transformer architectures, deep learning, regression, simulation, scenario analysis, clustering, decision trees, and more.
Experience with data science & ML workflows within cloud environments (training, evaluation, deployment).
Effective collaboration and communication skills, enabling seamless teamwork across departments and disciplines.

Nice To Haves

Experience with GCP and Airflow
Experience with PyTorch / Pandas / Python
Experience with Infrastructure as Code (Terraform / OpenTofu)
Experience with Software Engineering workflows (CI/CD, GitHub)
Experience with Docker/containerization
Familiarity with LLM / Agentic workflows
Security and/or game development experience
Experience with fraud detection & heavily imbalanced datasets

Responsibilities

Work with partners across the organization, gathering requirements, designing project plans, determining approaches, and defining success criteria for machine learning solutions.
Design, develop, deploy, and maintain machine learning solutions end-to-end in a cloud environment.
Implement and maintain model evaluation, monitoring, and observability.
Build integrations for machine learning models into game development pipelines.
Transform raw data and build efficient data pipelines to support modeling and analytical capabilities within our team.
Communicate the results of your analyses to both technical and non-technical colleagues.
Own solutions implementation & evaluation end-to-end