2027 AI Quant Summer Analyst

StepStone Group•San Diego, CA

About The Position

StepStone's AI & Quantitative Investment Research team applies artificial intelligence, quantitative methods, and proprietary data to investment research across private markets. The team works across investing, data, and technology to identify differentiated investment signals, strengthen portfolio insights, and develop practical decision-support tools. Research spans the full lifecycle, from framing investment questions and evaluating data to testing analytical approaches and communicating findings. The focus is on producing rigorous, explainable insights that inform investment judgment. The intern will support applied AI and quantitative research related to private markets, gaining hands-on exposure to investment questions, proprietary datasets, and collaboration with investment, data, and technology professionals. The role involves moving research from an initial question through analysis and interpretation, with an emphasis on thoughtful problem-solving, sound judgment, and clear communication. Projects may span multiple asset classes and contribute to investment selection, portfolio construction, monitoring, benchmarking, and risk assessment. The position is part of the 2027 summer intern program, with a preference for part-time remote work during the 2028 fall semester.

Requirements

Pursuing a bachelor's or master's degree in Mathematics, Statistics, Econometrics, Computer Science, Engineering, Data Science, Finance, Economics, or a related quantitative field.
Strong Python coding skills, including experience with data pipelines and quantitative modeling.
SQL proficiency.
Demonstrated ability to work with large, messy real-world datasets.
Strong problem-solving skills and intellectual curiosity, including willingness to challenge assumptions and investigate unexpected results.
Clear written and verbal communication skills, including the ability to explain technical concepts and analytical findings to investment stakeholders.
Openness to feedback and continuous improvement.
Willingness to contribute to work at all levels, including data preparation.

Nice To Haves

Advanced coursework or research experience in quantitative methods, machine learning, or empirical analysis.
Experience or coursework in AI/ML, including LLMs, NLP, data retrieval, or vector embeddings.
Ability to work in person in the La Jolla office during the 2027 summer intern program and part-time remotely during the 2028 fall semester.
Familiarity with cloud data platforms such as Snowflake or Azure, vector databases, or workflow orchestration tools such as Airflow.

Responsibilities

Support applied AI and quantitative research using proprietary data and institutional knowledge to identify investment signals, performance drivers, portfolio trends, and emerging risks across private markets.
Apply statistical, econometric, machine learning, and natural-language processing methods to structured and unstructured information, producing robust, explainable, and economically intuitive findings.
Work with investment, data, and technology stakeholders to translate investment questions into analytical approaches and connect findings to practical investment applications.
Document research approaches, assumptions, findings, and limitations.
Communicate conclusions clearly to technical and non-technical audiences, including investment stakeholders.
Contribute to research tasks at all levels, including data preparation and complex modeling.