Databricks: Data Science Intern (2027 Start) — Mountain View, California; San Francisco, California

Databricks lists a Data Science Intern (2027 Start) opening in Mountain View, California; San Francisco, California. The job description covers Python, SQL, Excel, data analysis, machine learning, AI, compliance.

Recruitment overview

OrganisationDatabricks
Post / roleData Science Intern (2027 Start)
DepartmentUniversity Recruiting - Engineering
Employment typeNot specified
Notification / job ID6866538002
Job locationMountain View, California; San Francisco, California
Work arrangementNot specified
Educational qualificationQualification references: PhD / doctorate
Experience requiredNo numeric experience requirement extracted; read the employer notice
Salary / stipendSee employer notice for pay details
Last date to applySee official notice

About Databricks

Databricks develops a platform for data, analytics and AI. Its employer material describes bringing related capabilities together so organisations can build and scale applications, analytics and agents using their information. The advertised platform portfolio includes data-engineering, lakehouse, governance and AI-related products. Its business connects the infrastructure used to manage data with the tools used to derive insights or create applications, rather than treating those activities as entirely separate technology projects.

The position and its setting

Databricks lists Data Science Intern (2027 Start) in Mountain View, California; San Francisco, California, under reference 6866538002. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

  • Department: University Recruiting - Engineering
  • Employer listing date: 18 August 2023

Responsibilities and work described

  • 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
  • Management: your own project end-to-end from data exploration to presenting insights to stakeholders and/or deployment an algorithm in a product environment

Essential requirements and candidate background

  • 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)
  • Ability to work with data in SQL and Python
  • Experience: 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

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

  • Advertised location: Mountain View, California; San Francisco, California

Benefits mentioned by the employer

  • 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

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Data Science Intern (2027 Start) vacancy is not an offer for reference 6866538002; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Databricks

Applications follow the official employer page linked below.

Open the official Databricks posting below and match the title and reference 6866538002.

Compare your qualifications and experience with the essential conditions for the Mountain View, California; San Francisco, California position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

  • Python
  • SQL
  • AI/ML
  • Excel
  • data analysis
  • machine learning
  • AI
  • compliance
  • sales

Important links

Official notification / job descriptionOpen official page

Read the complete official notice before applying. Availability and requirements can change.

For corrections, see our editorial policy and contact information.