Staff Data Scientist
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will shape data-science work across segmentation, recommendation systems, forecasting, product analytics, churn prediction, and insights. You will partner with business functions, manage stakeholder requirements and milestones, mentor junior data scientists, build self-service internal data products, and communicate results to technical and non-technical audiences.
Requirements
- 7+ years of data science, machine learning, or advanced analytics experience in high-velocity, high-growth companies
- Experience applying data science and machine learning to develop and deploy data-driven products
- Familiarity with product data science, including adoption, churn, cohorts, segmentation, and funnel analysis
- Experience collaborating with stakeholders across business functions
- Strong coding skills in Scala or Python and familiarity with testing, code review, and deployment
- Proficiency in data analysis and visualization using R and Python
- Experience with distributed data processing systems such as Spark and proficiency in SQL
- MS or Ph.D. in a quantitative field
Responsibilities
- Shape data science work across segmentation, recommendation systems, forecasting, product analytics, churn prediction, and insights
- Partner with Engineering, Product Management, Sales, and Customer Success to analyze usage patterns and make data-driven recommendations and forecasts
- Manage stakeholder requirements, project OKRs, milestones, and progress communication
- Mentor junior data scientists through project planning, technical decisions, and reviews
- Build self-service internal data products
- Represent the data science discipline throughout the organization
- Represent the organization at academic and industrial conferences and events
Benefits
- Annual performance bonus eligibility
- Equity eligibility