This Data Scientist role will oversee the design, development, and deployment of machine learning and analytical models used across the firm's investment research and decision‑support workflows. This includes ownership of the full project lifecycle: concept formation, exploratory analysis, model construction, validation, and integration into production environments.
About the Organization
The firm is a long‑term oriented private investment firm that actively partners with brand-name high‑growth companies solving complex, large‑scale problems across industries such as advanced manufacturing, next‑generation consumer products, aerospace, food systems, transportation, and emerging technology. It operates with a hands‑on approach rooted in operational excellence, supporting portfolio companies by working directly alongside founders, operators, and engineering teams.
About the Team
The Data team serves as an internal engine for data‑driven insight and product development. The group builds analytical tools that help identify promising opportunities, enhance evaluation frameworks, and provide quantitative support for investment and operational teams.
The team spans data science, research, and engineering disciplines, collaborating to create models and systems that push the boundaries of what is possible in applying advanced analytics to private markets and innovation‑centric sectors.
Role Overview
The Data Scientist will oversee the design, development, and deployment of machine learning and analytical models used across the firm's investment research and decision‑support workflows. This includes ownership of the full project lifecycle: concept formation, exploratory analysis, model construction, validation, and integration into production environments.
This individual will help evaluate unconventional and emerging datasets, extract insights from complex information sources, and continuously improve existing internal products. The role also plays an important part in fostering a culture of rigorous thinking, disciplined methodology, and continuous improvement.
Qualifications
• Bachelor's, Master's, or Ph.D. in a quantitative discipline
• 2+ years of relevant industry experience (excluding internships)
• Strong proficiency in Python and SQL
• Strong understanding of statistics, machine learning, optimization, and applied mathematics
• A collaborative and low‑ego working style, with strong commitment to high‑quality output
Preferred Experience
• Experience with quantitative modeling, signal generation, or portfolio‑related research in private or public market equities
• Familiarity with cloud platforms, containerization, or workflow orchestration tools (e.g., GCP, Docker, Prefect)
