Senior Systematic Risk Manager

Balyasny Asset Management L.P. (BAM) is a global institutional investment firm. We strive to deliver consistent, uncorrelated, absolute returns in all market environments by fostering a culture of research, innovation, and collaboration. BAM exists at the intersection of finance and technology, combining the deep industry knowledge of leading portfolio managers and financial analysts with software engineers and quantitative researchers. We leverage the collective expertise of our teams to seek out new investment opportunities, analyze market conditions, minimize risk, and provide superior service to our investment partners. With 1900+ people in 20 offices around the world, we embrace a culture that welcomes the free flow of ideas, promotes career development, and supports the health and wellbeing of our people through world-class benefits. ROLE OVERVIEW We are looking for a senior Risk Manager to support our growing global Systematic Trading business: Conduct daily and intraday analysis on the Systematic portfolios. Review process, architecture, simulation and backtest methodologies for Systematic portfolios. Refine the process of manager selection and performance assessment, with a keen focus on macro/thematic drivers and crowding analysis Develop methodologies and metrics for risk managing Systematic portfolios with a focus on shorter term strategies; build tools to monitor these and share with PMs. Contribute to BAM's risk analytics, processes and reporting both within the Systematic business and elsewhere. Build relationships with systematic PMs both in US and globally. Build relationships with systematic business management including the Global Head of Systematic Provide input and participate in weekly Global Risk committee discussions; make recommendations to Investment Committee where appropriate. Advise on whether BAM is being sufficiently rewarded for the risks it takes. Report to Co-heads of Systematic and Event Risk Requirements: Strong academic background with an advanced degree (Masters or Doctorate) in a quantitative discipline such as Math, Physics, Computer Science, Financial Engineering 10 or more years relevant experience in the quantitative finance field, with roles such as risk manager / portfolio manager / quant trader in a major bank, hedge fund, or quantitative trading firm Strong programming skills in Python or C++/C# Well-versed in equity statistical arbitrage Familiar with equity factor models Strong communication skills. The role involves constant dialogue with all parts of the organisation Rigorous research and analytical skills. Creative, motivated, hard-working, and strong all-around interest in financial markets. Practical approach to problem solving. Attention to detail - takes ownership of projects, strong focus on data quality, correctness, and intuitiveness of output. Nice to have: Knowledge of execution algorithms Knowledge of market microstructure Knowledge of transaction cost modelling Knowledge of systematic macro strategies Experience applying LLMs or Machine Learning to systematic trading Operational Risk