Quantitative Researcher - Index Rebal | Global Fund


Shanghai
Permanent
Negotiable
Financial Technology
PR/596472_1781244516
Quantitative Researcher - Index Rebal | Global Fund

Quantitative Researcher - Index Rebalancing | Global Fund

About the Role

A leading global hedge fund is seeking a Quantitative Researcher to join its Index Rebalancing team. The role focuses on researching, developing, and implementing systematic trading strategies around global index rebalancing events. You will work closely with Portfolio Managers, traders, and data teams in a fast-paced, front-office environment.

Key Responsibilities

  • Research & signal development - Conduct quantitative research on global index rebalancing events (e.g., MSCI, FTSE, S&P), passive fund flows, and flow-driven strategies to identify alpha-generating opportunities
  • Predictive modeling - Build and refine models to forecast index constituent changes, estimate market impact, and capture pre- and post-rebalancing inefficiencies
  • Strategy implementation - Translate research into live systematic trading strategies; backtest, deploy, and monitor performance with rigorous PnL attribution
  • Data & infrastructure - Work with large-scale datasets (tick data, corporate actions, index constituent histories) and contribute to the team's research and production infrastructure
  • Collaboration - Partner with PMs, execution traders, and data engineering teams to optimize trade construction, execution, and strategy scalability across global markets
  • Innovation - Apply machine learning, AI tools, and advanced statistical techniques to enhance research, forecasting, and execution workflows

Requirements

  • Education - Bachelor's, Master's, or PhD in a quantitative field (Mathematics, Statistics, Physics, Computer Science, Engineering, or similar)
  • Experience - 2+ years in a quantitative research role with direct exposure to index rebalancing, index arbitrage, or closely related systematic equities strategies
  • Technical skills - Strong programming ability in Python (C++ a plus); proficiency with SQL, Pandas, NumPy, and large-scale data manipulation; Linux environment experience preferred
  • Domain knowledge - Solid understanding of global index methodologies, trade construction, and systematic risk management
  • Analytical mindset - Demonstrated ability to independently generate trade ideas, formulate complex problems, and make data-driven decisions
  • Communication - Excellent verbal and written communication skills; ability to present research findings clearly to PMs and senior stakeholders

FAQs

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