Location: New York,NY, USA
The Firm:
Our client is a top alternative investment manager that manages capital for well-known private, public, and non-profit institutions worldwide. With an emphasis on learning and teamwork, our client has fostered a culture that brings together highly skilled quantitative researchers from across the globe. These researchers are given the freedom to independently explore their ideas and create practical solutions that enhance their professional development and make a real difference.
They are looking to speak with impact-driven and motivated individuals currently in their penultimate year of their PhD (expected graduation in 2026).
The Internship:
In the field of quantitative research, you will encounter challenging tasks and apply sophisticated statistical techniques to analyse complex financial markets, which are known for their intricate datasets.
As an Quantitative Research intern, you will participate in an 11-week program where you can collaborate and interact with senior team members. You will also have the chance to network and socialize with your peers throughout the internship.
Day-to-Day:
• Conceptualize valuation strategies, develop and continuously improve upon mathematical models, and help translate algorithms into code
• Back test and implement trading models and signals in a live trading environment
• Use unconventional data sources to drive innovation
• Conduct research and advanced mathematical analysis to build and refine monetization systems for trading signals
Basic Qualifications:
• Currently undertaking a PhD in Mathematics, Statistics, Physics, Computer Science, or another highly quantitative field with an expected completion date in 2025 and strong academic performance
• Strong knowledge of probability and statistics (e.g. machine learning, time-series analysis, pattern recognition, NLP)
• Background working in a data driven research environment
• Experience with NoSQL databases (e.g. MongoDB), distributed computing (e.g. MapReduce), and/or analytical packages (e.g. R, Matlab) would be beneficial
Pre-Application