Coinbase off campus Data science intern Hiring 2023

November 7, 2023

Coinbase Off-Campus data science intern 2023 Hiring Details:

At Coinbase, our mission is to increase economic freedom around the world, and we couldn’t do this without hiring the best people. We’re a group of hard-working overachievers who are deeply focused on building the future of finance and Web3 for our users across the globe, whether they’re trading, storing, staking or using crypto. Know those people who always lead the group project? That’s us.

There are a few things we look for across all hires we make at Coinbase, regardless of role or team. First, we look for candidates who will thrive in a culture like ours, where we default to trust, embrace feedback, and disrupt ourselves. Second, we expect all employees to commit to our mission-focused approach to our work. Finally, we seek people who are excited to learn about and live crypto, because those are the folks who enjoy the intense moments in our sprint and recharge work culture. We’re a remote-first company looking to hire the absolute best talent all over the world.

Ready to #LiveCrypto? Who you are:

• You’ve got positive energy. You’re optimistic about the future and determined to get there. 

• You’re never tired of learning. You want to be a pro in bleeding edge tech like DeFi, NFTs, DAOs, and Web 3.0. 

• You appreciate direct communication. You’re both an active communicator and an eager listener - because let’s face it, you can’t have one without the other. You’re cool with candid feedback and see every setback as an opportunity to grow.

• You can pivot on the fly. Crypto is constantly evolving, so our priorities do, too. What you worked on last month may not be what you work on today, and that excites you. You’re not looking for a boring job.

• You have a “can do” attitude. Our teams create high-quality work on quick timelines. Owning a problem doesn’t scare you, but rather empowers you to take 100% responsibility for achieving our mission.

• You want to be part of a winning team. We’re stronger together, and you’re a person who embraces being pushed out of your comfort zone.

As a part of the Strategy, Execution, & Analytics team, you’ll spend part of your time collaborating closely with business partners in product and engineering teams — to ensure we’re focused on the biggest opportunities and interpreting our data correctly. You’ll also work with the data engineering team to build analytics models and systems that help scale our insights more broadly, both throughout the company and directly in the product. We expect you to demonstrate clear communication, a strong desire to execute, and best-in-class craftsmanship.

Note: Internship period Jan - June

What you’ll be doing (ie. job duties):

• Collaborate with functional teams to support analyses and modeling that prioritizes opportunities and provides insights.

• Assist in designing and conducting experiments/analysis to measure impact and suggest potential product improvements.

• Support the team in measuring business performance and help refine core metrics.

• Contribute to data-driven storytelling, distilling complex analyses into clear, actionable insights.

• Participate in analytical deep dives alongside senior team members to understand and address complex business problems.

• Assist in the development and maintenance of data pipelines, ensuring data integrity and accuracy.

What we look for in you (ie. job requirements):

• Some experience or coursework related to data analysis, statistical modeling, or other related fields.

• Basic understanding of statistical concepts and a keen interest in furthering this knowledge (in A|B testing, causal inference, ML, etc.).

• Familiarity with data analysis using SQL is a plus.

• Some experience or coursework in programming/modeling, preferably in Python.

• An embodiment of our core cultural values: clear communication, positive energy, continuous learning, and efficient execution.

Nice to haves:

• Degree or currently pursuing a Bachelor/Masters degree in a quantitative field (ex Math, Stats, Physics, or Computer Science).

• Exposure or interest in data engineering.

• Eagerness to delve into varying levels of data work to understand and improve foundational data structures.

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