Job Description

We are seeking highly motivated and talented people to join the Boerboel team. As a member of the team you will be working with passionate and curious colleagues who thrive on solving complex problems. Boerboel is an office-first firm. While we offer flexibility to our employees, remote work is not available at this time.


As a

Quantitative Researcher,

you'll use a rigorous scientific method to develop sophisticated investment models and shape our understanding of market behavior. You'll explore large datasets, generate hypotheses, and partner closely with different members of the team to turn research into reality.

Objectives:

Use statistical modeling, optimization, and machine learning techniques to analyze large and diverse datasets Create and test complex investment and trading models across multiple asset classes Work with engineers to implement and backtest models in live trading environments Design experiments and analyze real-world results to refine hypotheses and improve performance Stay current with new research in statistics, machine learning, and quantitative finance Contribute to discussions that help shape the direction of our firm's quantitative research strategy

Qualifications:

Demonstrated ability and experience through internship or academic projects (0-2 years) Bachelor's, Master's, or Ph.D. in a technical or quantitative discipline such as Statistics, Mathematics, Physics, Electrical Engineering, Computer Science, or related field (graduating Dec 2025 - June 2026) Strong foundation in probability, statistics, linear algebra, and data analysis Intermediate programming skills (Python or C++) Experience conducting research or independent projects involving data analysis, modeling, or algorithm development Strong analytical and critical thinking skills with a creative approach to problem-solving Excellent written and verbal communication skills -- able to present complex ideas clearly and succinctly Curiosity about financial markets (no prior finance experience required)

Preferred:

Hands-on experience with machine learning frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Exposure to time-series analysis, signal processing, or stochastic modeling Familiarity with data visualization tools (Matplotlib, Plotly, ggplot, etc.) Coursework or research in econometrics, game theory, or optimization Academic or open-source research publications



This position is eligible to be based in Chicago, IL, New York, NY or London, UK. In compliance with applicable U.S. pay transparency laws, the anticipated base range for this role is $100,000-$175,000 annually in Chicago, IL and New York, NY. Pay (base and bonus) may vary depending on job-related skills and experience. A discretionary performance bonus may be provided as part of the total compensation package.


Eligible employees can participate in our benefits package which include health insurance, retirement savings plan, PTO, etc. Offerings may differ depending on location.