Quantitative Researcher - London, United Kingdom - Jane Street
Description
About the Position:
As a Quantitative Research intern, you'll work side by side with full-timers to learn how we identify market signals, analyze large datasets, build and test models, create new strategies, and write code to implement them.
The problems we work on rarely have clean, definitive answers—and they often require insights from colleagues across the firm with different areas of expertise.
Some projects consider big-picture questions that we're still trying to figure out, while others involve building new tools or systems.
Your mentors will work in two distinct areas of research, so you'll gain a better understanding of the diverse array of research challenges we consider every day, from reasoning about how best to analyze very noisy datasets to building practical models that allow us to better identify market signals.
Your day-to-day project work will be complemented by classes on the broader fundamentals of markets and trading, lunch seminars, and real-time discussion on the desk.
During the second half of the internship, you will also get to participate in one "elective" based on your interests.
Algorithmic Trading and Market Microstructure:
You'll learn the end-to-end process of developing an algorithmic trading strategy.
Working in small teams, you'll learn how to analyze market data to develop a tradable fair value, implement a trading strategy in Python, and adapt that strategy to different market structures.
Teams will compete to have the best performing strategy in several different simulated markets.Through classes and immersive activities, you'll also learn how to backtest your strategy and improve its performance from simulation, and how real-world trading differs from simulation.
Modeling, Machine Learning, and Data Science:
About You:
We don't expect you to have a background in finance or any other specific field—we're looking for smart people who enjoy solving interesting problems.
You should be:
- Intellectually curious—asking great questions is more important than knowing all the answers
- A strong programmer who is interested in learning to write code in OCaml, even if you've never done functional programming before
- An openminded thinker and precise communicator who enjoys interacting with colleagues from a wide range of professional backgrounds and areas of expertise
- Eager to ask questions, admit mistakes, and learn new things
- Fluent in English
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