Quantitative Researcher

Jane Street

$120K — $180K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong programming skills in Python
  • Experience with data science or machine learning techniques
  • PhD or equivalent research experience preferred
  • Logical and mathematical problem-solving abilities
  • Intellectual curiosity and a willingness to learn

Responsibilities

  • Build models and strategies for pricing and trading financial instruments
  • Collaborate closely with researchers, engineers, and traders
  • Design experiments and generate datasets
  • Conduct time series analysis and feature engineering
  • Study model performance in production environments
  • Tweak hyperparameters and debug distributed training processes
  • Analyze market data with advanced statistical techniques

Benefits

  • Collaboration with experienced researchers and a diverse team
  • Opportunities for continuous learning and professional development
  • Access to cutting-edge technology and large datasets
  • Exciting problem-solving environment in finance
  • Supportive atmosphere for career changers and those new to finance
Full Job Description
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. 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, but ultimately, we're more interested in how you think and learn, than what you currently know. PhD or other research experience is a plus. If you'd like to learn more, you can read about our interview process and meet some of the team.

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