Role Details

Location

US - Remote Zone 1 (Job Requisitions Only)

Salary (est. USD)

~$231K - $363K (est. USD)

Estimated based on role seniority, company stage (Public), and industry benchmarks. Actual compensation may vary.

How is this calculated?

Seniority band Senior / Lead

Domain premium Quant / Trading (+50%)

Base range $210K – $330K

Stage adjustment Public (+10%)

Adjusted range $231K – $363K

Based on Web3 & AI industry compensation data. Seniority is inferred from role title keywords. Company stage affects ranges: early-stage (−15%), late-stage/public (+10%).

Department

Data Science

Type

Full-time

Vertical

Exchange

Hiring Manager

Best Guess

Job Description

Ready to be pushed beyond what you think you’re capable of?

At Coinbase, our mission is to increase economic freedom in the world. It’s a massive, ambitious opportunity that demands the best of us, every day, as we build the emerging onchain platform — and with it, the future global financial system.

To achieve our mission, we’re seeking a very specific candidate. We want someone who is passionate about our mission and who believes in the power of crypto and blockchain technology to update the financial system. We want someone who is eager to leave their mark on the world, who relishes the pressure and privilege of working with high caliber colleagues, and who actively seeks feedback to keep leveling up. We want someone who will run towards, not away from, solving the company’s hardest problems.

Our work culture is intense and isn’t for everyone. But if you want to build the future alongside others who excel in their disciplines and expect the same from you, there’s no better place to be.

While many roles at Coinbase are remote-first, we are not remote-only. In-person participation is required throughout the year. Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and fully supported.

Data Science is an integral component of Coinbase’s product and decision making process: we work in partnership with Product, Engineering and Design to influence the roadmap and better understand our users. With a deep expertise in experimentation, analytics and advanced modeling, we produce insights which directly move the company’s bottom line.

The Retail Trading Data Science team plays a critical role in shaping the strategy and performance of the retail trading platform. The team partners closely with cross-functional stakeholders to define key metrics, analyze user behavior, design and evaluate experiments, and develop models that improve product performance and customer outcomes. By leveraging data to uncover insights into trading behavior, market dynamics, and platform performance, the team informs key business decisions and drives improvements in engagement, trading activity, and long-term customer value.

What you'll be doing:

Conduct analysis and deep dives on ambiguous problems for our business. Your work will result in insights and recommendations that guide the team’s decision making.
Act as owner for a broad scope of data and metrics, from core logging to presentation of data visualizations.
Guide code reviews, provide SQL and Python expertise, and create well-maintained ETL jobs.
Maintain a high bar for statistical rigor on your team. Ensure that we’re conducting experimentation and causal analyses that build confidence with your stakeholders.
Synthesize findings, and recommendations in a clear and concise manner and communicate to senior leadership.

What we look for in you:

A BA/BS in a quantitative field (ex Math, Stats, Physics, or Computer Science) with ≥5+ years of relevant experience or a PhD in a quantitative field with with ≥3+ years of relevant experience
Demonstrated experience in driving impactful data science projects that tackle ambiguous problem spaces.
Drive end-to-end experimentation, from design through execution and analysis, to maximize insights and guide future product investments
Ability to influence external stakeholders by synthesizing data learnings into compelling stories.
Practical expertise in applying complex modeling frameworks to practical business problems.
Professional experience using SQL and Python.
Demonstration of our core cultural values: clear communication, positive energy, continuous learning, and efficient execution.
Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.

Disclaimer: Applying for a specific role does not guarantee consideration for that exact position. Leveling and team matching are assessed throughout the interview process.