The role is for a data scientist on the Trust and Safety Data Science team at Databricks, focusing on ensuring the security and compliance of the Databricks Platform. The team works on critical projects that involve statistical and machine learning techniques for fraud and abuse detection. This position requires collaboration with engineering and security teams to develop solutions that protect customer data. The ideal candidate will have a strong background in data science and machine learning, with a focus on compliance and security.

• 7+ years of data science, machine learning, and advanced analytics experience in high-velocity, high-growth companies
• Understanding of good software engineering practices around testing, code reviews, and deployment
• Experience working in a highly cross-functional alignment and communicating results to non-technical partners
• Experience deploying Data Science / ML solutions in production to achieve results
• Coding skills in SQL and a software development language, preferably Python
• Experience with distributed data processing systems like Spark and familiarity with software engineering principles
• Masters or higher in quantitative fields or equivalent experience in industry

• Develop and implement Machine Learning models to detect anomalous activity in products offered by Databricks
• Analyze the performance and pricing of security-related features and work with product and engineering teams to identify important opportunities
• Collaborate with security engineers, trust and safety experts, and machine learning engineers to build systems and tools that protect Databricks and its customers from threats
• Create solutions and frameworks to meet compliance requirements at Databricks
• Gather requirements, define project OKRs and milestones, and communicate progress to both technical and non-technical audiences
• Guide junior data scientists and interns on the team by helping with project planning, technical decisions, and code and document review
• Represent the data science discipline throughout the organization, promoting a data-driven culture
• Represent Databricks at academic and industrial conferences and events