Quantitative Analyst Intern

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.

Internship Responsibilities

As a Quantitative Analyst Intern at Seldon Capital, you will:

• Build and test quantitative models to forecast asset returns, volatility, and regime shifts across equities, rates, FX, and commodities

• Perform statistical analysis on large, noisy financial and alternative datasets

• Develop features from raw market, macroeconomic, and company-level data

• Research and implement machine learning techniques for prediction, classification, and signal generation

• Evaluate model robustness through backtesting, cross-validation, and sensitivity analysis

• Assist in portfolio construction, risk modeling, and position sizing frameworks

• Collaborate with fundamental analysts and traders to translate economic hypotheses into quantitative signals

• Write clean, production-quality research code in Python

• Document assumptions, methodology, and results clearly for internal review

Who You Are

We are looking for candidates who demonstrate:

• Strong quantitative intuition and comfort working with probability, statistics, and linear algebra

• Genuine interest in financial markets and how data reflects real-world economic behavior

• Ability to reason rigorously about uncertainty, signal vs. noise, and model limitations

• Curiosity and independence in exploring new datasets, techniques, and hypotheses

• High technical standards for code correctness, clarity, and reproducibility

• Clear written and verbal communication skill

Technical Skills (Strongly Preferred)

• Proficiency in Python (NumPy, pandas, SciPy; scikit-learn or PyTorch a plus)

• Experience working with time series data

• Familiarity with statistical modeling, regression, and hypothesis testing

• Exposure to machine learning methods such as tree-based models, regularization, or neural networks

• Comfort working in a research-oriented codebase (Jupyter, Git, Linux environment)

Preferred Background

• Pursuing a Bachelor’s, Master’s, or PhD in Mathematics, Statistics, Computer Science, Physics, Engineering, Economics, or a closely related field

• Demonstrated excellence in quantitative coursework

• Prior experience in quantitative research, trading, data science, or applied ML is a plus

• Participation in math, statistics, or programming competitions (e.g., Kaggle, ICPC, Putnam, Olympiad-level work) is a plus

• Familiarity with financial data platforms (Bloomberg, FactSet) is helpful but not required

What We Offer

• Direct exposure to real hedge fund quantitative research and decision-making

• Opportunity to work on problems that directly impact capital allocation

• Mentorship from senior investors, quants, and traders with top-tier hedge fund backgrounds

• A high bar, intellectually honest research environment

• Potential for a full-time Quantitative Analyst role based on performance

Seldon Capital is an equal opportunity employer. We welcome applicants from all backgrounds and are committed to fostering an inclusive work environment.