Staff Data Scientist - Trust and Safety

Databricks Databricks · Data AI · San Francisco, CA · Engineering - Pipeline

Staff Data Scientist focused on Trust and Safety at Databricks, developing and implementing ML models for fraud and abuse detection, analyzing security features, and collaborating with engineering and security teams to protect the platform and customers. The role involves creating compliance solutions, gathering requirements, and guiding junior team members.

What you'd actually do

  1. You will develop and implement Machine Learning models to detect anomalous activity in products that we offer.
  2. You will analyze the performance and pricing of security-related features and work with product and engineering teams to identify important opportunities.
  3. You will collaborate with security engineers, trust and safety experts, and machine learning engineers to build a variety of systems and tools that protect Databricks and our customers from threats.
  4. You will create solutions and frameworks to meet compliance requirements at Databricks
  5. You will gather requirements, define project OKRs and milestones, and communicate progress to both technical and non-technical audiences.

Skills

Required

  • 7+ years of data science, machine learning, and advanced analytics experience
  • Understanding of good software engineering practices around testing, code reviews, and deployment.
  • Experience working in a highly cross functional alignment and talking about 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

Nice to have

  • Prior experience applying machine learning and data analytics to identify SaaS product misuse and enhance compliance

What the JD emphasized

  • 7+ years of data science, machine learning, and advanced analytics experience in high-velocity, high-growth companies
  • Experience deploying Data Science / ML solutions in production to achieve results.

Other signals

  • Develop and implement Machine Learning models to detect anomalous activity
  • Apply machine learning and data analytics to identify SaaS product misuse
  • Fraud and abuse detection