Level

Coinbase

Data Science Intern

Coinbase is hiring a Data Science Intern in San Francisco, United States. It pays $50/hr and Level rates it ; you can apply on Coinbase.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • The posting allows some remote work.
  • Tools and skills the posting cites include SQL, Python and statistical modeling.
  • Level classifies it as an internship.
  • Level lists 226 other open roles at Coinbase.

AI in this role

Build analytical models, support A/B testing, and maintain data pipelines as a data science intern.

sqlpython
statistical-modelinga-b-testingcausal-inferencemachine-learningdata-pipelines

Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase.

This is a 12-week internship during summer 2027.

As a Data Science Intern on the Strategy, Execution, & Analytics team within the Platform group, you'll partner with product and engineering teams to turn data into decisions that drive real business impact. This team builds analytics models and systems that scale insights across Coinbase and directly into the product. You'll collaborate with senior data scientists and business partners to design experiments, build models, and deliver data-driven recommendations that shape how millions of customers experience crypto. You will gain hands-on experience at a publicly traded crypto-native company, with mentorship from senior data scientists and direct exposure to how data shapes the company.

What you'll do:

  • Collaborate with product teams to create analyses and build models that drive measurable business outcomes.
  • Support the design and execution of experiments, including A/B tests and causal inference methods.
  • Build and maintain analytical datasets and pipelines that ensure data integrity and power your analyses and models.
  • Distill complex analyses into clear, actionable insights through data-driven storytelling for technical and non-technical audiences.
  • Partner with senior team members on analytical deep dives to diagnose and address complex business problems.

Required Skills and Experience:

  • Coursework or project experience in statistical modeling, data analysis, or a related quantitative field (e.g., mathematics, economics, physics, computer science).
  • Familiarity with SQL for data analysis and Python for programming or modeling.
  • Demonstrated interest in experimentation (A/B testing), causal inference, or machine learning through coursework or projects.
  • Currently pursuing a BA/BS or graduate degree in a quantitative discipline (e.g., Math, Statistics, Physics, Computer Science, Economics) or equivalent experience.
  • Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

 

Req ID: P78149

#LI-Hybrid

Pay Transparency Notice: Depending on your work location, the target hourly rate for this position can range as detailed below.   Hourly Rate:$50—$50 USD
  • Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.
  • Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws.
  • US Applicants: View Employee Rights, Know Your Rights, and E-Verify Notice of Participation.
  • Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial.
  • Data Privacy & Arbitration: By submitting your application, you agree to our Candidate Privacy Notice. US applicants: By submitting your application, you agree to Arbitration of Disputes.

How we rate this

Data Science Intern at Coinbase rates 30 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Statistical ModelingA B TestingCausal InferenceMachine learningData PipelinesSQLPython

Questions you could be asked

  1. Tell me about a project where statistical modeling was part of your work. What did you do?
  2. Tell me about a project where a b testing was part of your work. What did you do?
  3. Tell me about a project where causal inference was part of your work. What did you do?
  4. Tell me about a project where machine learning was part of your work. What did you do?
  5. Tell me about a project where data pipelines was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Statistical Modeling, A B Testing, Causal Inference, Machine learning, and Data Pipelines. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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