Quantitative Researcher Intern (Summer 2022)
Walleye Capital is a technology-driven hedge fund with over $2.5B of investor capital. Walleye has more than 170 employees in six offices across the US trading in equity, options, futures, and foreign exchange markets. We employ outstanding quant researchers, engineers, and traders who have built some of the most sophisticated trading systems in the world.
Walleye Capital is hiring a Quantitative Researcher Intern to work in our quantitative strategies team in Boston. We are a tight-knit, collaborative, and intellectually rigorous team responsible for managing a number of systematic trading strategies in equity statistical arbitrage, volatility arbitrage, and futures. We are looking for talented coders who can rapidly prototype and test improvements to our quantitative investment strategies. You will join a team where your creativity, initiative, and teamwork will make direct impacts on trading profits.
What will you do?
· Work on 1-3 specific coding projects for the duration of the internship across many stages of the investment process.
· Partner with team members to build and improve our infrastructure and tools for trading, risk management and attribution.
· Extract and analyze large amounts of historical data from a variety of structured and unstructured sources.
· Design and test new predictive signals, data sets or trading strategies.
· Build machine learning systems used to predict patterns in asset returns, risks, trading costs, or other aspects relevant to managing our portfolios.
· Significant coding in Python and/or R.
What are you like?
· Demonstrated programming proficiency, particularly in R and/or Python.
· Pursuing a bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a similar discipline.
· An independent thinker who can build creative approaches to complex problems and articulate those ideas clearly through verbal, written, and visual media.
· Strong quantitative, analytical, and programming skills; preferably demonstrated by real-world research projects and/or code repositories.
· Experience with databases and query languages preferred.
· Passion for financial markets, investing, and trading.