At least 5 years of relevant professional experience in index rebalancing or related fields.
Demonstrated experience in quantitative research focused on equity-index rebalancing.
Strong understanding of equity-index methodologies and reconstitution processes.
Proficiency in Python, particularly with libraries like pandas and NumPy.
Solid command of statistical modeling and empirical research design.
Bachelor's degree or higher in a quantitative discipline.
Responsibilities
Lead quantitative research initiatives on equity-index rebalances and related events.
Analyze index methodologies to identify trading opportunities and risk factors.
Develop and enhance systematic models for forecasting rebalance flows and trading costs.
Design and maintain Python-based tools for data processing and portfolio construction.
Build portfolio-optimization frameworks balancing return, liquidity, and risk constraints.
Conduct historical analysis and back-testing to refine strategies.
Collaborate with portfolio managers to translate research into actionable trade ideas.
Benefits
Mentorship opportunities for junior team members.
Access to advanced research infrastructure and tools.
Collaborative work environment with senior investors and portfolio managers.
Full Job Description
Overview
The Equity Index Rebalancing team is seeking an experienced Index Analyst to lead research, modeling, and implementation work across systematic equity-index rebalancing strategies. This individual will work closely with senior investors and portfolio managers to evaluate index methodologies, identify and monetize rebalance-related opportunities, and enhance portfolio-construction and execution processes.
The ideal candidate will have experience in equity-index rebalancing, index arbitrage, ETF/index portfolio management, or a closely related quantitative investing role. They should combine strong research judgment with hands-on Python development, statistical analysis, optimization, and a detailed understanding of index events, methodology changes, corporate actions, and liquidity dynamics.
Responsibilities
Own quantitative research initiatives related to equity-index rebalances, including additions/deletions, reconstitutions, corporate actions, methodology changes, and other index-driven events.
Analyze index methodologies and rule changes to identify implementation implications, trading opportunities, risk factors, and potential sources of crowding.
Develop, test, and enhance systematic models for forecasting rebalance flows, price impact, liquidity, trading costs, and post-event performance.
Design and maintain robust Python-based research and production tools for data processing, signal generation, portfolio construction, and monitoring.
Build and improve portfolio-optimization frameworks that balance expected return, benchmark exposure, liquidity, turnover, transaction costs, concentration, and risk constraints.
Conduct rigorous historical analysis, back-testing, and attribution to evaluate new ideas and improve existing strategies.
Partner with portfolio managers and traders to translate research findings into actionable trade ideas and implementation plans.
Develop market monitors, relative-value screens, and dashboards to track upcoming rebalance events, estimated flows, positioning, liquidity, and realized outcomes.
Evaluate relevant legal, regulatory, index-provider, and corporate-action documentation; translate key terms and event mechanics into quantitative inputs and portfolio implications.
Help establish robust research standards, including data validation, model documentation, monitoring, and post-trade review.
Mentor junior team members and contribute to the development of the team's research infrastructure and investment process.
Qualifications & Requirements
At least 5 years of relevant professional experience in index rebalancing, index arbitrage, ETF/index portfolio management, quantitative equity research, systematic trading, or a related role.
Demonstrated experience conducting quantitative research specifically related to equity-index rebalancing, including index events, constituent changes, methodology-driven flows, or benchmark-tracking portfolios.
Strong understanding of major equity-index methodologies, reconstitution and rebalance processes, corporate actions, free-float adjustments, share changes, and index-provider event mechanics.
Programming ability in Python, including experience with pandas, NumPy, SciPy, optimization libraries, and production-quality research workflows is preferred
Strong command of statistical modeling, time-series analysis, hypothesis testing, back-testing methodology, and empirical research design.
Bachelor's degree or higher in a quantitative discipline, such as mathematics, statistics, computer science, engineering, physics, economics, or finance.
About Balyasny Asset Management L.P.
Balyasny Asset Management L.P. is a global investment firm that manages hedge funds and private investment funds. The company was founded in 2001 by Dmitry Balyasny and is headquartered in Chicago, Illinois, with additional offices in New York, London, Hong Kong, and Singapore. Balyasny Asset Management L.P. employs a multi-strategy approach to investing and focuses on generating alpha through a combination of fundamental analysis and quantitative research. The company has a strong track record of performance and has received numerous awards for its investment strategies.
