Associate Quantitative Trader, Voleon Securities

Responsibilities

• Monitor automated execution and portfolio risk during U.S. market hours, and respond to alerts, exceptions, and incidents.
• Track real-time developments across the credit, rates, and ETF markets we trade.
• Design and build the data pipelines, dashboards, and analytics that measure execution quality, monitor data health, and surface abnormal production behavior.
• Apply statistical analysis to production and research data to produce actionable insights into our trading, and automate the analyses worth monitoring over time.
• Contribute to the codebase underlying automated trading operations, and build processes and technology that prevent errors and outages while increasing the desk's capacity.
• Interface with clients, electronic trading venues, and clearing and financing counterparties.
• Provide market and data expertise to research and strategy partners.
• Help extend the desk into new asset classes and markets, such as equities and futures.
• Obtain and maintain the FINRA licenses required for the role (e.g., Series 7/57).

Requirements

• Demonstrated experience and passion for financial markets, with an ability to work in a high ownership, fast-paced startup environment.
• Proficiency, experience, and understanding of Python and SQL used for data analysis (beyond purely utilizing gen-AI tools).
• Hands-on experience working with complex datasets end to end: curation, querying, aggregation, exploratory data analysis, and visualization.
• A solid foundation in statistics — the ability to frame and answer questions mathematically, identify patterns, and reason carefully about distributions, sample sizes, and uncertainty.
• Comfort working in a Unix-like environment (command line, shell, git).
• Strong data-visualization and communication skills: the ability to turn an ambiguous question into a clear, well-supported answer.
• Attention to detail and clarity of thought, with rigor about cause and effect.
• A bachelor's degree in a quantitative or scientific discipline (e.g., statistics, data science, computer science, engineering, mathematics, economics, or a related field).

Preferred Requirements

• A master's degree, or one or more years of applied data, engineering, or trading experience (including internships).
• Experience trading fixed income, or applied market microstructure knowledge.
• Experience building data pipelines or production-facing tooling (ETL, workflow orchestration such as Airflow, CI/CD, git).
• Fluency with data libraries (pandas or Polars and a plotting library) and analytical data stores (e.g., DuckDB, Parquet).
• Exposure to the FIX protocol or electronic trading systems.