Quantitative Researcher

Equity Statistical Arbitrage Quantitative Researcher - Leading Global Hedge Fund Location - New York Description: Our client is a leading global multi-strategy hedge fund with a highly sophisticated systematic and quantitative investment platform. The firm works with some of the most established Portfolio Managers and investment teams in the industry, providing them with significant capital, technology, data and quantitative infrastructure. As part of the continued growth of one of its high-performing equity investment pods, the firm is looking to hire an experienced Equity Statistical Arbitrage Quantitative Researcher to focus directly on alpha generation. This is a front-office research role for a researcher who wants to work closely with a successful investment team and have a direct impact on the development and implementation of systematic equity strategies. The Opportunity: The successful candidate will join an established and high-performing equity pod, working alongside experienced Portfolio Managers, researchers and traders. The focus will be on identifying new sources of systematic alpha across equity markets, with significant ownership over the research process from initial idea generation through to implementation. This is not a pure academic or supporting research role. The successful candidate will be expected to generate differentiated signals, develop robust quantitative models and contribute directly to live trading decisions and portfolio performance. Key Responsibilities: Conduct quantitative research to identify new sources of alpha across global equity markets. Develop systematic statistical arbitrage signals, models and trading strategies. Analyse large and complex financial datasets to identify persistent market inefficiencies. Develop and test predictive models using advanced statistical and quantitative techniques. Design robust backtesting methodologies and evaluate strategy performance. Work closely with Portfolio Managers to translate research into live trading strategies. Contribute to portfolio construction, signal combination and risk management. Continuously monitor live strategies and identify opportunities to improve performance. Develop new research methodologies and approaches to enhance the pod's alpha generation capabilities. Collaborate with other quantitative researchers, traders and technology professionals within the investment team. Ideal Candidate: We are looking for an experienced Equity Statistical Arbitrage Quantitative Researcher with: 5+ years of experience in quantitative research, systematic trading or alpha generation. Experience working at a leading hedge fund, proprietary trading firm or systematic investment manager. An advanced degree, ideally a PhD or equivalent, in Mathematics, Statistics, Computer Science, Physics, Engineering or another highly quantitative discipline. A proven track record of generating alpha within equity markets. Strong expertise in statistical arbitrage and systematic equity strategies. Exceptional statistical, mathematical and analytical capabilities. Strong programming skills, ideally in Python, C++ or similar languages. Experience working with large-scale financial datasets and developing predictive models. Strong understanding of backtesting, signal development and systematic strategy construction. Demonstrated ability to take research from initial hypothesis through to live implementation. Strong communication skills and the ability to work closely with Portfolio Managers in a high-performance environment. A highly intellectually curious and rigorous approach to quantitative research. The Environment: The successful candidate will join a high-performing investment pod where quantitative research is directly connected to trading and PnL generation. The role offers the opportunity to work closely with an established PM and investment team, with access to significant data, technology, execution and risk infrastructure. The emphasis is on developing differentiated alpha and delivering research that can translate directly into live systematic trading strategies. #J-18808-Ljbffr