Quantitative Researcher

We are looking for Quantitative Researchers tohelp us build models, strategies, and systems thatprice and trade financial instruments. You'll workside by side with experienced researchers who arecommitted to teaching, guiding, and supporting ournewest hires, learning how we think aboutexperiment design, dataset generation, time seriesanalysis, feature engineering, and model buildingfor financial datasets.

At Jane Street, our researchers, engineers, andtraders sit a few feet away from each other andwork together to train models, architect systems,and run trading strategies. We work with petabytesof data, a computing cluster with hundreds ofthousands of cores, and a growing GPU clustercontaining tens of thousands of high-end GPUs.Depending on the day, we might be diving deep intomarket data, tuning hyperparameters, debuggingdistributed training performance, or studying howour model likes to trade in production.

We don't believe in "one-size-fits-all"modelling solutions; we are open to and excitedabout applying all different types of statisticaland ML techniques, from linear models to deeplearning, depending on what best fits a givenproblem. The most successful researchers will bedriven by a curiosity for how their contributionsfit into the larger picture of our tradingoperations, and how to adapt their findings intoactionable strategies.

If you've never thought about a career infinance, you're in good company. Many of us werein the same position before working here. If youhave a curious mind and a passion for solvinginteresting problems, we have a feeling you'll fitright in. You should be:

• Able to apply logical and mathematicalthinking to all kinds of problems
• Intellectually curious; eager to askquestions, admit mistakes, and learn new things
• A strong programmer who's comfortablewith Python
• An open-minded thinker and precisecommunicator who enjoys collaborating withcolleagues from a wide range of backgrounds andareas of expertise

Most candidates will have experience with datascience or machine learning, but ultimately, we'remore interested in how you think and learn thanwhat you currently know. PhD or other researchexperience is a plus.

If you'd like to learn more, you can read aboutour interview process and meet some of the team onour website.

Computer Science, Data, AI,Engineering & Technology,Life and Health Sciences, Medicine,Natural Sciences & Mathematics

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