Quantitative Researcher, Mid-Long Horizon Equities (Alpha)
- 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.
- 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.
- 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.
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