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SeniorFull-timePythonMachine LearningData ScienceGitAIData
Salary Range
$104,975 - $142,025 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Senior Data Scientist to join our Institutional team at Coinbase. This role involves supporting the foundations for the Coinbase Institutional business by building models and frameworks to explore fee schedules, analyzing and improving frameworks around Prime Broker Trading/Financing offerings, and getting involved in efforts such as Custody, Web3 & Staking to help onboard Institutions in their DeFi journey.
Key Responsibilities
- →Conduct analysis and deep dives on ambiguous problems for our business, resulting 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, ensuring that we’re conducting experimentation and causal analyses that build confidence with stakeholders.
Requirements
- ✓A BA/BS in a quantitative field (e.g., Math, Stats, Physics, or Computer Science) with ≥5+ years of relevant experience or a PhD in a quantitative field with ≥3+ years of relevant experience.
- ✓Demonstrated experience in driving impactful data science projects that tackle ambiguous problem spaces.
- ✓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.
- ✓Experience working with digital products in an iterative development cycle.
- ✓Demonstration of our core cultural values: clear communication, positive energy, continuous learning, and efficient execution.
- ✓Ability to responsibly use generative AI tools and copilots 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.
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