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Senior Data Scientist

San Francisco, California💼 Full-time💰 $123,200–$123,200🗓 2026-05-27 → 2026-08-01

Core

Shape data science direction for usage forecasting, product analytics, and user behavior analysis to drive data-driven decisions and forecasts.

Role type

Senior Data Scientist (Product Analytics & Strategy)

Builds

Self-serving internal data products and data-driven decision frameworks for the Databricks Data Team.

Domain

SaaS / Data & AI Infrastructure / Product Analytics

Deliverable

product features

Required skills

Production ML application, Product Analytics (adoption, churn, cohorts, funnel), Stakeholder management, Distributed data processing (Spark, Hadoop), SQL, General purpose coding (Scala/Python), Data visualization (R/Python)

Preferred skills

Software engineering principles (testing, code reviews, deployment)

Technologies

Apache Spark, Hadoop, Scala, Python, R, SQL

Responsibilities

Shape direction of key data science areas (usage forecasting, product analytics, user behavior), Collaborate with Product, Sales, and Customer Success to understand usage patterns, Manage stakeholders and define project OKRs/milestones, Mentor junior data scientists on planning and technical decisions, Build self-serving internal data products.

Seniority

Senior, hands-on IC with mentorship

Rewrite
## Responsibilities - Shape the direction of some of our key data science areas for 2020 - usage forecasting, product analytics, user behavior and funnel analysis. - Work closely with Product Management, Sales, Customer Success and other stakeholders to understand product usage patterns and trends and to make data-driven decisions and forecasts. - Manage stakeholders for their focus area - gather changing requirements, define project OKRs and milestones, and communicate progress and results to a non-technical audience. - Mentor and guide data-scientists on the team by helping with project planning, technical decisions, and code and document review. - Build self-serving internal data products to make data simple within the company. ## Requirements - Experience in applying Data Science / ML in production to build data-driven products for solving business problems. - Familiarity with Product Analytics - understanding and tracking customer and user behaviour using lenses like adoption, churn, cohorts and funnel analysis. - Experience collaborating with and understanding the needs of stakeholders from a variety of business functions. We work most closely with Product, Customer Success and Engineering at the moment, but also work with the Sales, Marketing and Finance organizations. - Strong coding skills in general purpose languages like Scala or Python, and familiarity with software engineering principles around testing, code reviews and deployment. - Proficient in data analysis and visualization using tools like R and Python. - Experience with distributed data processing systems like Spark and Hadoop, and proficiency in SQL. - BS/MS/PhD in Computer Science, or a related field ## Nice to Have - None specified ## Benefits - Databricks is the data and AI company. More than 5,000 organizations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world's toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. ## Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
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