Quantitative Researcher

Jane Street • New York, NY

10h • Onsite

About The Position

We are looking for Quantitative Researchers to help us build models, strategies, and systems that price and trade financial instruments. You’ll work side by side with experienced researchers who are committed to teaching, guiding, and supporting our newest hires, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets.
At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and work together to train models, architect systems, and run trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing tens of thousands of high-end GPUs. Depending on the day, we might be diving deep into market data, tuning hyperparameters, debugging distributed training performance, or studying how our model likes to trade in production.
We don’t believe in “one-size-fits-all” modeling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep learning, depending on what best fits a given problem. The most successful researchers will be driven by a curiosity for how their contributions fit into the larger picture of our trading operations, and how to adapt their findings into actionable strategies.

Requirements

• Strong programmer comfortable with Python.
• Open-minded thinker and precise communicator.
• Enjoys collaborating with colleagues from a wide range of backgrounds and areas of expertise.

Nice To Haves

• Experience with data science or machine learning.
• PhD or other research experience is a plus.

Responsibilities

• Build models, strategies, and systems that price and trade financial instruments.
• Apply logical and mathematical thinking to all kinds of problems.
• Design experiments, generate datasets, perform time series analysis, engineer features, and build models for financial datasets.
• Train models, architect systems, and run trading strategies.
• Dive deep into market data, tune hyperparameters, debug distributed training performance, and study model behavior in production.
• Apply statistical and ML techniques, from linear models to deep learning.
• Adapt findings into actionable strategies.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed