MachineLearning Quantitative Researcher

STORMLIGHT CAPITAL; Chicago (IL); Remote; USD 100,000 - 160,000; Full time

Job summary

A leading high-frequency trading firm is seeking a researcher to develop systematic trading signals from large datasets. This remote role offers the opportunity to work closely with portfolio managers and engineers to innovate and implement advanced trading strategies from day one. Ideal candidates will possess advanced degrees in quantitative fields and expertise in Python, machine learning, and NLP.

Benefits

Bonus based on performance

Flexible schedule

Home office stipend

Opportunity for advancement

Paid time off

Profit sharing

Signing bonus

Qualifications

• Track record of designing repeatable experiments with statistical validation.
• Comfort manipulating TB-scale datasets and proficiency with distributed frameworks.
• Hands-on experience with large language models and classical NLP pipelines.

Responsibilities

• Spearhead research initiatives transforming datasets into trading signals.
• Build and compare NLP architectures and develop statistical models.
• Present findings to senior leadership and contribute to research culture.

Skills

Expert-level Python

Statistical modeling

Machine learning

Natural Language Processing

Data handling

Communication

Education

M.S. or Ph.D. in Computer Science

M.S. or Ph.D. in Statistics

M.S. or Ph.D. in Physics

M.S. or Ph.D. in Electrical Engineering

M.S. or Ph.D. in Applied Math

Tools

Spark

Dask

Git

Job description

Benefits:

Bonus based on performance

Flexible schedule

Home office stipend

Opportunity for advancement

Paid time off

Profit sharing

Signing bonus

About Stormlight Capital

Stormlight Capital LLC is a high-frequency trading firm and market maker specializing in event contracts. Leveraging advanced technology and quantitative expertise, we deliver deep liquidity, efficient pricing, and robust risk management for our proprietary trading strategies. Continuous innovation and disciplined execution keep us at the forefront of event-based markets.

Role Summary

You will spearhead research initiatives that transform large‑scale textual and structured datasets into systematic trading signals. Working closely with portfolio managers, data engineers, and software developers, you will own the full research lifecycle—from idea generation and data acquisition through model development, back‑testing, and hand‑off to production.

What You’ll Do

Identify predictive patterns in alternative textual and tabular data sources

Mine time‑series and cross‑sectional relationships in high‑frequency and daily tabular data

Build and compare NLP architectures (transformers, embeddings, topic & sentiment models)

Develop statistical and machine‑learning models (linear factor, tree‑based, gradient boosting, neural nets) that combine text‑derived features with numeric factors

Construct robust, transaction‑cost‑aware back‑tests

Partner with Data Engineering to scale data pipelines and feature stores

Work with Portfolio Engineering to integrate signals into systematic strategies and monitor live performance

Present findings to senior leadership; contribute to Stormlight’s research culture through white‑papers, internal talks, and code reviews

Minimum Qualifications

Education – M.S. or Ph.D. in Computer Science, Statistics, Physics, Electrical Engineering, Applied Math, or a related quantitative field

Programming – Expert‑level Python (pandas, NumPy, PyTorch or TensorFlow, scikit‑learn); solid SQL; version control (git)

NLP & ML – Hands‑on experience training and fine‑tuning large language models, embeddings, and classical NLP pipelines; strong grasp of supervised learning, regularization, cross‑validation, and hyper‑parameter optimization

Data Handling – Comfort manipulating TB‑scale datasets; proficiency with Spark, Dask, or comparable distributed frameworks

Research Rigor – Track record of designing repeatable experiments, performing thorough statistical validation, and communicating uncertainty

Communication – Ability to translate complex technical concepts into clear, actionable insights for stakeholders

Preferred/Bonus Skills

Prior alpha‑research or risk‑modeling experience in equities, futures, options, or FX

Familiarity with market microstructure and execution cost modeling

Contributions to open‑source ML/NLP projects or published research

Why Stormlight

Impact from Day 1 – Your models feed directly into active portfolios

Research‑First Culture – time for blue‑sky experimentation; regular reading groups

Competitive Total Compensation – Base salary, performance‑linked bonus, and profit‑share.

Flexibility – Hybrid schedule or fully remote in a US‑friendly time zone

This is a remote position.