Data Scientist, Technical Lead

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.

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.

Preferred Qualifications

• Experience building or growing high-performing data science teams in production-aware or high-stakes settings.
• Exposure to financial markets, trading systems, or quantitative research environments.
• Familiarity with production monitoring systems, data quality pipelines, or analytics platform development.
• 7+ years of experience managing data scientists.
• Experience managing a large team or multiple teams.