We are partnered with a boutique alternative investment firm looking to expand its Quantitative Research team. This group sits at the intersection of investing, technology, and data science, building proprietary research tools, systematic ranking models, risk management frameworks, and alpha-generating signals that directly support investment decisions across a flexible small- and mid-cap equity strategy. The role offers the opportunity to help shape the firm's data strategy, work with alternative datasets, and drive new quantitative initiatives alongside a lean, high-impact team.

Responsibilities:

Research and develop proprietary alpha factors, systematic ranking models, and investment signals using fundamental and alternative datasets. Analyze large and diverse datasets, including financial, fundamental, and alternative data, to uncover actionable investment insights. Enhance and expand existing research infrastructure, portfolio analytics tools, and quantitative systems while helping build new capabilities from the ground up. Partner closely with portfolio manager, fundamental analysts, and technology stakeholders to improve portfolio construction, risk management, and investment decision-making. Build tools and frameworks that support factor analysis, custom hedging strategies, portfolio monitoring, and investment research workflows.

Requirements:

3+ years of experience in quantitative research, data science, machine learning, or systematic investing. Strong understanding of factor investing, alpha research, statistical analysis, and data-driven investment processes. Advanced programming skills in Python, including experience working with large datasets and modern data science libraries. Experience developing proprietary signals, quantitative models, or research tools using fundamental and/or alternative data. Knowledge of factor risk models, portfolio analytics, or systematic investment strategies is highly preferred.