Quantitative Researcher
Overview
Seldon Capital is a San Francisco-based hedge fund advancing the craft of investing through deep fundamental research and machine learning. We specialize in forecasting boom-and-bust cycles driven by technological change, industry disruption, and government policy. Our portfolio spans long and short positions across equities, fixed income, currencies, and commodities. The firm was founded by former senior investors from Soros Fund Management, with prior experience at leading institutions including Lone Pine Capital, Goldman Sachs, Balyasny, and Coatue.
Role Summary
We are seeking a Fundamental Analyst to uncover deep value, special situations, and event-driven opportunities across global public equity and credit markets.
Responsibilities
Design and maintain robust ETL pipelines for ingesting and transforming financial data
Engineer domain-specific features from raw datasets to support macro and sector-level analysis
Collaborate on the development of machine learning infrastructure and backtesting frameworks
Automate high-leverage workflows across research and operational functions
Analyze structured data to improve model accuracy and support investment decision-making
Qualifications
Advanced degree in Computer Science or a related technical field
3+ years of experience in data engineering, quantitative research, or applied data science
Strong Python skills with a focus on writing clean, production-grade code
Experience with SQL, Pandas, Elasticsearch, and Kibana
Familiarity with APIs, time-series modeling, and ML tools such as XGBoost and Random Forest
Proven ability to automate and scale research infrastructure
Interest in forecasting or ML competitions (e.g., Kaggle, Metaculus) is a plus
Compensation
Highly competitive compensation, benefits, and annual performance-based bonus, commensurate with experience.
Seldon Capital is an equal opportunity employer. We welcome applicants from all backgrounds and are committed to fostering an inclusive workplace.
