Quantitative Researcher, Mid-Long Horizon Equities (Alpha)

Responsibilities

• Conduct original research to identify and develop alpha signals across global equity markets.
• Utilize alternative and non-market datasets to uncover predictive relationships and differentiated sources of return.
• Design, test, and validate medium-long term signals with holding periods generally exceeding one week.
• Develop novel features, predictive models, and forecasting frameworks that can be translated into live trading strategies.
• Perform deep statistical analysis to evaluate signal efficacy, robustness, decay profiles, and interaction effects.
• Partner closely with portfolio managers to drive the alpha generation process from idea inception through production deployment.
• Explore new datasets and research methodologies to continuously expand the team's opportunity set.
• Monitor live signals and identify opportunities for enhancement and optimization.

Requirements

• 5+ years of experience in quantitative research within a hedge fund, asset manager, alpha capture team, or systematic investing platform.
• Proven track record of developing alpha signals that have contributed meaningfully to trading or investment performance.
• Significant experience working with alternative data and non-market datasets.
• Deep understanding of alpha research, signal development, and predictive modeling within equities.
• Strong programming skills in Python and experience working with large-scale datasets.
• Excellent knowledge of statistics, machine learning, and empirical research methodologies.
• Demonstrated ability to independently generate and test investment hypotheses.
• Strong intellectual curiosity and a passion for uncovering unique sources of alpha.

Preferred Background

• Experience within a systematic equities, alpha capture, or quantitative stock selection team.
• Track record monetizing alternative datasets in live investment strategies.
• Expertise analyzing datasets such as consumer transactions, web traffic, job postings, product data, geolocation, supply chain, app usage, earnings-related data, or other proprietary information sources.
• Experience building predictive models for earnings expectations, revenue forecasting, company fundamentals, analyst revisions, or medium-term stock returns.
• Previous experience operating within a pod-based investment framework at a hedge fund or proprietary trading firm.