# Staff Data Scientist - Trust and Safety

**Company:** [Databricks](https://hotfix.jobs/companies/databricks)
**Location:** San Francisco, CA
**Role:** Data Science
**Salary:** $192K-$260K
**Experience:** 7+ years
**Skills:** Machine Learning, Python, SQL, Spark, Data Science, Software Engineering, Fraud Detection, Anomaly Detection, Distributed Systems, Production Ml
**Posted:** 2026-01-30

> Develops ML models for fraud/abuse detection and anomalous activity on Databricks platform. Analyzes security features, collaborates cross-functionally, and deploys production solutions. Requires 7+ years experience, MS in quantitative field, Python/SQL/Spark expertise.

## Job Description

## Impact You Will Have
- Develop and implement Machine Learning models to detect anomalous activity in products.
- Analyze the performance and pricing of security-related features and work with product and engineering teams to identify opportunities.
- Collaborate with security engineers, trust and safety experts, and machine learning engineers to build systems and tools that protect Databricks and customers from threats.
- Create solutions and frameworks to meet compliance requirements.
- Gather requirements, define project OKRs and milestones, and communicate progress to technical and non-technical audiences.
- Guide junior data scientists and interns on project planning, technical decisions, and code review.
- Represent the data science discipline organization-wide to drive data-driven decisions.
- Represent Databricks at academic and industrial conferences.

## What We Look For
- **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 cross-functionally and communicating results to non-technical partners.
- Experience deploying Data Science / ML solutions in production.
- Coding skills in **SQL** and a software development language (**Python** preferred).
- Experience with distributed data processing systems like **Spark** and familiarity with software engineering principles.
- Prior experience applying machine learning and data analytics to identify SaaS product misuse and enhance compliance (preferred).
- **Masters or higher** in quantitative fields or equivalent industry experience.

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