Quantitative Research (Machine Learning) Intern at Summit Securities Group – Chicago, Illinois

Human Intuition. Machine Intelligence. Relentless Exploration.
Exceptional trading emerges where human intuition meets frictionless experimentation. Our platform and processes enable traders to rapidly investigate ideas, identify emergent patterns, and convert insights into live strategies. This synthesis creates a flywheel of discovery — the key to our pursuit of excellence.
The Role:
We are looking for a Quantitative Research Intern to help build machine learning-driven statistical arbitrage and high-frequency trading strategies in U.S. equities. You will work closely with our senior researchers, using large-scale data and quantitative models to predict short-term price movements, design models, and capture market inefficiencies.
Responsibilities:

• Alpha & Strategy Research: Explore, model, and validate new predictive signals using large, complex datasets.
• Machine Learning Application: Apply advanced machine learning and deep learning architectures to uncover hidden patterns and inefficiencies in financial markets.
• Rigorous Validation: Stress-test your hypotheses, identify hidden biases, and analyze model performance using the team’s backtesting frameworks.
• Collaborative Innovation: Participate in technical discussions and present your research findings to the broader team.

You Bring:

• Education: Currently in penultimate or final year of a PhD program in a highly quantitative field such as Computer Science, Statistics, Mathematics, Physics, or Engineering (minimum 3.5 GPA required).
• Required Skills:
  • Programming: Strong proficiency in Python and its scientific computing stack (Pandas, NumPy, SciPy, scikit-learn).
  • Deep Learning: Practical experience building and training RNN (Recurrent Neural Network) and Transformer architectures.
  • Machine Learning: Hands-on experience with predictive modeling, including regression, classification, clustering, as well as bagging and boosting algorithms (e.g., XGBoost, LightGBM).
• Behavioral: Strong intellectual curiosity paired with low ego. A relentless drive to find the truth in data, the ability to clearly defend your research methodology, and the eagerness to learn how theoretical models translate to financial markets.
• Competitive Pedigree: Demonstrated success in competitive environments, such as AI/machine learning competitions (e.g., Kaggle) or programming competitions (e.g., ICPC, Putnam).

We Offer:
At our firm, our people come first. We are committed to building a culture of collaboration, where we support each other through challenges and celebrate our collective successes. We believe that the strength of a modern workplace lies in its diverse workforce—diverse in ideas, cultures, and experiences. We actively foster this environment and take pride in being an equal opportunity employer. The estimated weekly base salary for this role is $3,350.
While we value flexibility, we believe that in-person collaboration is key to solving complex challenges, which is why we require employees to be in the office 4 days a week. In-office perks include lunch and a great location with amazing colleagues.
Our top priority is our people. We invest in a culture that promotes togetherness, helping each other through challenges and celebrating each other's successes. We believe that modern workplaces succeed by having diverse high-performance workforces — in ideas, in cultures, and in experiences. We put in the effort to make such a workplace a daily reality and are proud to be an equal opportunity employer.