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About the Role

We are seeking Quantitative Researchers to develop models, strategies, and systems for pricing and trading financial instruments. You will collaborate with experienced researchers, learning about experiment design, data generation, time series analysis, feature engineering, and model building for financial datasets. Our environment fosters close collaboration between researchers, engineers, and traders, utilizing vast datasets and extensive computing resources. We embrace diverse statistical and ML techniques, from linear models to deep learning, and value researchers driven by curiosity and the ability to translate findings into actionable strategies.

Responsibilities

Build models, strategies, and systems that price and trade financial instruments.
Design experiments, generate datasets, perform time series analysis, and engineer features.
Build models for financial datasets.
Dive deep into market data.
Tune hyperparameters.
Debug distributed training performance.
Study model trading behavior in production.
Apply statistical and ML techniques, including linear models and deep learning.
Adapt findings into actionable strategies.

Requirements

Able to apply logical and mathematical thinking to all kinds of problems.
Intellectually curious; eager to ask questions, admit mistakes, and learn new things.
A strong programmer who’s comfortable with Python.
An open-minded thinker and precise communicator who enjoys collaborating with colleagues from a wide range of backgrounds and areas of expertise.
Fluent in English.
Experience with data science or machine learning is common, but thinking and learning ability are prioritized.
PhD or other research experience is a plus.

Skills

Python programming
Logical thinking
Mathematical thinking
Data science
Machine learning
Experiment design
Dataset generation
Time series analysis
Feature engineering
Model building
Communication
Collaboration

Education Level

PhD or other research experience is a plus.

About the Company

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.
We don’t believe in “one-size-fits-all” modelling 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.
If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here.
If you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in.