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Senior Data Scientist

Databricks· Data Team
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Hybrid (Mountain View / San Francisco)$123.2k - $218kfull-timePosted 5mo ago

About the role

Data Scientist on the Data Team at Databricks, focused on solving product and business challenges with data-driven approaches, building internal data products, and mentoring other data scientists.

Responsibilities

  • Shape the direction of key data science areas for 2020 (usage forecasting, product analytics, user behavior and funnel analysis)
  • Work with Product Management, Sales, Customer Success and other stakeholders to understand product usage and forecast trends
  • Manage stakeholders for focus areas: gather requirements, define OKRs and milestones, communicate progress to non-technical audiences
  • Mentor and guide data scientists on project planning, technical decisions, and code/document reviews
  • Build self-serving internal data products to simplify data access within the company

Qualifications

  • Experience in applying Data Science / ML in production to build data-driven products solving business problems
  • Familiarity with Product Analytics (adoption, churn, cohorts, funnel analysis)
  • Ability to collaborate with stakeholders from Product, Customer Success, Engineering, Sales, Marketing and Finance
  • Strong coding skills in Scala or Python, with testing, code reviews and deployment experience
  • Proficiency in data analysis and visualization using R and Python
  • Experience with distributed data processing systems like Spark and Hadoop, and proficiency in SQL
  • BS/MS/PhD in Computer Science or related field

Skills

Required:Data Science / ML in productionProduct AnalyticsStakeholder managementCodingData analysis & visualizationDistributed data processing

Benefits

  • Benefits details available through company page or regional document (link provided in description)
Last updated Sep 10, 2026. Interested? Apply on the company site.

About Databricks

Leading Data and AI Platform for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

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