About the posting
“As a Data Science Intern, you will join the Data team of data scientists and engineers to turn Databricks business and operations data into insights for product design, strategies for customer acquisition/retention, and optimizations to engineering system efficiency/stability/performance.”
Read the full posting on Databricks' site
Seen live Oct 23, 2026; first seen Oct 23, 2026.
Pay in context
Databricks does not list pay for this role. 85 percent of data and analytics postings in San Francisco, CA do; their median is $210,500.
How long it has been open
Posted Aug 17, 2023, 1163 days ago, and seen on Databricks' careers page today.
At 1163 days old, it is over the 67-day median.
Databricks' postings we have seen close took a median of 7 days.
Databricks at a glance
Databricks has 494 open postings that we can see, 8 in data and analytics; 95 percent list pay.
The application
Applying goes through Greenhouse.
Trailhead fills Greenhouse, Lever and Ashby forms on your computer; on the phone and on other systems it hands you your answers and your resume.
Seniority
Level: entry.
Place and cost of living
On site in San Francisco, CA; prices in CA run 11 percent above the US average.
The data and analytics market in San Francisco, CA
199 data and analytics postings in San Francisco, CA are open right now, from 92 employers.
Half of them have been open 67 days or less.
From Databricks' posting
This is Databricks' own text, as published on its job board. We last checked it on Oct 23, 2026. Apply on Databricks' site. We remove a posting when the employer closes it.
(P-972)
At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.
As a Data Science Intern, you will join the Data team of data scientists and engineers to turn Databricks business and operations data into insights for product design, strategies for customer acquisition/retention, and optimizations to engineering system efficiency/stability/performance. The Data team also functions as an internal "customer" that dogfoods the Databricks platform and drives product improvements.
We are hiring for the Mountain View & San Francisco offices. We will discuss more with you as you move through the process!
The Impact You Will Have
- Work with the Data team and internal stakeholders (Product, Customer Success, Engineering, Sales, Marketing and Finance) to use data to solve problems
- Apply your expertise in data science methodologies such as causal inference modeling and recommender systems to real data to deliver insights and/or deploy algorithms to the Databricks platform
- Manage your own project end-to-end from data exploration to presenting insights to stakeholders and/or deployment an algorithm in a product environment
What We Look For
- You will graduate in fall 2027 or spring 2028 with a Master's or PhD degree in a quantitative field (e.g., Statistics, Math, Computer Science, Physics, Economics, Operational Research or Engineering)
- Proven ability to work with data in SQL and Python
- Experience with multiple statistical data analysis and machine learning methods such as generalized linear regression, regression and classification trees, unsupervised learning methods, causal inference, stochastic processes, time series forecasting
- You are excited to solve ambiguous problems with a collaborative team
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here .
SF Bay Area Hourly Rate
$54 — $60 USD
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram .
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here .
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.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.