Quantitative Researcher

London Source: WhatJobs
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We are looking for Quantitative Researchers to help us build models, strategies and systems that price and trade financial instruments. You'll apply your experience in experiment design, dataset generation, time series analysis, feature engineering and model building to financial datasets, while collaborating with colleagues who will challenge and refine your approach.

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 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” modelling solutions; we are open to and excited about applying all different types of statistical and machine learning 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.

About You

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. You should be:

  • 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

Most candidates will have experience with data science or machine learning, though your approach to problem-solving and capacity to learn will weigh just as heavily as your existing expertise. Having a PhD or other research experience is a plus.

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