Staff Data Scientist, Infrastructure: Scale & Reliability

Neon; Mountain View (CA); On-site; USD 192,000 - 260,000; Full time

Job summary

Databricks, a leading data and AI company, seeks a seasoned Data Scientist to join the Data Team in Mountain View, CA. You will build data science tooling to enable rapid, data‑driven decision making and partner with Data Platform and Product Engineering to extend capabilities across the core platform.

You will own insights generation for top priorities, mentor junior scientists, and represent the team at academic and industry events, shaping the future direction of our products and workflows.

Qualifications

• 7+ years of data science, ML, analytics in high-velocity environments.
• Experience deploying data science/ML to production to build data-driven products.
• Collaborating with senior leaders from Engineering, Product, Operations.
• Ability to handle ambiguity and craft 0-to-1 solutions.
• Strong Python/SQL coding; familiarity with distributed data processing.
• MS or PhD in quantitative fields.

Responsibilities

• Build data science tooling to inform decision making for leaders, analysts, and data scientists.
• Extend data science capabilities with Data Platform and Product Engineering teams.
• Lead insights generation for top company priorities and key initiatives.
• Define project OKRs and milestones, communicate progress to technical and non-technical audiences.
• Mentor junior data scientists and review code and documentation.
• Represent the data science function at conferences and internal events.

Skills

Python

SQL

Spark

Data tooling

Data storytelling

Education

MS or PhD in quantitative fields

Tools

Spark

Job description

Databricks, a leading data and AI company, seeks a seasoned Data Scientist to join the Data Team in Mountain View, CA. You will build data science tooling to enable rapid, data‑driven decision making and partner with Data Platform and Product Engineering to extend capabilities across the core platform.

You will own insights generation for top priorities, mentor junior scientists, and represent the team at academic and industry events, shaping the future direction of our products and workflows.