Quantitative Trader, Voleon Securities

Voleon Securities, a new business within the Voleon Group, provides liquidity in securities markets. We apply state-of-the-art AI/ML techniques to construct our liquidity-provision strategies. For nearly two decades, our affiliate Voleon Capital Management has led the hedge fund industry and worked at the frontier of applying AI/ML to investment management, becoming a multibillion-dollar asset manager. Voleon Securities builds on Voleon’s deep real-world experience applying ML to financial markets.

Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.

As an Associate Quantitative Trader, you will learn the business from the ground up: how our automated market-making system operates, how each asset class and venue we trade behaves, and how we measure and improve our trading. You will help run the desk day to day — monitoring live trading and risk, ensuring accurate strategy behavior, and decomposing our trading into the factors driving it — while spending the majority of your time on project work: building the data pipelines, analytics, and automation that raise the sophistication and scale at which the desk operates.

Under mentorship from senior traders, you will grow with the desk as it expands into new markets, and you will develop deep expertise in market microstructure, electronic execution, and the data and statistics that underpin them.

This is a hands-on, quantitative role in a fast paced, start-up environment. A large part of the work is curating and querying complex datasets, performing exploratory and statistical analysis, and communicating your findings clearly to traders, research, and leadership. The role is in office and follows U.S. market hours, with a shared on-call rotation.

• 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 counter parties

• 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)

• 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)

• A…