Voleon is seeking a Technical Lead in Data Science to guide the design, implementation, and evolution of analytical systems and mentor a growing team of data scientists to solve real-world problems in finance using AI and machine learning.
Requirements
- 3+ years of experience managing data scientists, including responsibility for performance development, technical direction, and project execution.
- 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.
- Familiarity with production monitoring systems, data quality pipelines, or analytics platform development.
Responsibilities
- Provide technical direction and management for a team of data scientists working on high-impact problems across trading and research systems.
- Shape analytical frameworks, ensuring methodological rigor, and delivering insights that inform business and research decisions.
- Own investigations of complex production behaviors and design robust methods for identifying, analyzing, and communicating system anomalies.
- 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.
Other
- 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.
- Demonstrated ability to lead cross-functional data initiatives, translate business objectives into analytical goals, and ensure timely delivery.
- Experience communicating complex findings to executive and technical stakeholders, including presenting insights, tradeoffs, and recommendations.
- 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.
