Data Scientist, Technical Lead
New
Remote-USAFull-TimeLead
Salary195000 - 225000 USD per year
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Job Details
- Experience
- 3+ years of experience managing data scientists, 7+ years of experience managing data scientists
- Required Skills
- SQLBashGitAirflowPandasCI/CDR
Requirements
- Master’s degree or higher in a quantitative, technical, or analytical field such as Data Science, Statistics, Computer Science, Engineering, Finance, or an MBA with strong analytical training
- 3+ years of experience managing data scientists, including responsibility for performance development, technical direction, and project execution
- Demonstrated ability to lead cross-functional data initiatives, translate business objectives into analytical goals, and ensure timely delivery
- Strong understanding of data science fundamentals, including statistical analysis, data preparation, root cause investigation, and the proven ability to guide others' work in these areas
- Familiarity with data tooling and workflows (e.g., SQL, Pandas, R, Airflow), with enough fluency to review and support technical contributors effectively
- Basic software development skills and experience with bash, linux/unix, and git
- Experience communicating complex findings to executive and technical stakeholders, including presenting insights, tradeoffs, and recommendations
- Track record of establishing scalable methodologies, driving technical standards, and fostering collaboration in fast-paced, analytically rigorous environments
Responsibilities
- Collaborate with Technical Product Owners in Research and Engineering to define priorities, scope solutions, and deliver actionable insights to stakeholders
- Own investigations of complex production behaviors and design robust methods for identifying, analyzing, and communicating system anomalies
- Mentor and manage junior and mid-level data scientists; provide architectural oversight for data projects
- Serve as a technical authority within the data science function, set standards for data quality, statistical rigor, and reproducibility
- Lead the design, development, and deployment of analytical pipelines to monitor and interpret production behavior across trading and research systems, ensuring its correctness
- Champion best practices in data governance, tooling, and collaborative development (CI/CD, version control, code reviews)
- Drive continual growth and learning within the team by onboarding new Data Scientists, growing teams, and fostering a culture of curiosity, collaboration, and applied experimentation
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