About the position
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. In this role, you will work closely with the Data team and internal stakeholders from various departments including Product, Customer Success, Engineering, Sales, Marketing, and Finance to leverage data in solving complex problems. You will apply your expertise in data science methodologies such as causal inference modeling and recommender systems to real data, delivering insights and deploying algorithms to the Databricks platform. You will manage your own project from start to finish, which includes data exploration, presenting insights to stakeholders, and deploying algorithms in a product environment. This internship is an excellent opportunity to gain hands-on experience in a dynamic and innovative company.
Responsibilities
- Work with the Data team and internal stakeholders to use data to solve problems.
- Apply expertise in data science methodologies such as causal inference modeling and recommender systems to real data.
- Manage your own project end-to-end from data exploration to presenting insights to stakeholders and/or deploying an algorithm in a product environment.
Requirements
- You will graduate in fall 2025 or spring 2026 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.
- Excitement to solve ambiguous problems with a collaborative team.
Benefits
- Annual performance bonus eligibility
- Equity options
- Comprehensive health benefits
- Flexible work hours
- Diversity and inclusion initiatives
