Global Stock Selection Research - Analyst/Associate

AQR•Greenwich, CT

22h•$165,000 - $200,000

About The Position

AQR is a global investment firm built at the intersection of financial theory and practical application. We strive to deliver concrete, long-term results by looking past market noise to identify and isolate the factors that matter most, and by developing ideas that stand up to rigorous testing. By putting theory into practice, we have become a leader in alternative strategies and an innovator in traditional portfolio management since 1998. At AQR, our employees share a common spirit of academic excellence, intellectual honesty and an unwavering commitment to seeking the truth. We’re determined to know what makes financial markets tick – and we’ll ask every question and challenge every assumption. We recognize and respect the power of collaboration, and believe transparency and openness to new ideas leads to innovation. The Global Stock Selection (GSS) group is responsible for the portfolio management and research of AQR's strategies relating to individual equities and equity related securities across all global liquid markets. GSS models are applied to market-neutral long/short portfolios in AQR hedge funds as well as to long-only, relaxed-constraint and low volatility portfolios for institutional equity mandates and mutual funds. AQR Capital Management is seeking a talented Researcher to join our team of professionals and focus on our proprietary strategies related to global stock selection. Candidates should be motivated and enthusiastic about implementing new ideas and are expected to be hands-on and self-sufficient in conducting all aspects of research projects. Researchers manage all aspects of the research process including data ingestion and processing, analysis, methodology selection, implementation, testing and performance evaluation. The role will involve collaboration with other researchers, portfolio managers, risk managers and traders to develop new and improve current investment strategies.

Requirements

B.S. degree from a top institution in computer science, engineering, mathematics, statistics, operations research, physics or another quantitative discipline
2-5 years’ experience working in a data driven research environment with an alpha focus
Proficient programming in Python required
Ability to manipulate large financial data sets for empirical research and handle complex
Strong quantitative skills with demonstrated understanding of mathematics, probability, statistics and linear algebra
Nuanced understanding of economic and financial concepts and demonstrated intuition around applying these concepts in a quantitative environment
Ability to work independently as well as part of a team
Demonstrated ability to express and articulate ideas and thought processes in both verbal and written form

Nice To Haves

Academic or practitioner experience in machine learning methodologies preferred
Experience in quantitative research at a top asset manager or hedge fund preferred
Experience with translating mathematical models and algorithms into code
Experience with machine learning software libraries such as scikit-learn, TensorFlow or PyTorch
Experience with natural language processing technology, including LLMs and prompt engineering is a plus

Responsibilities

Engage in alpha research and other quantitative analysis to improve current investment strategies in collaboration with existing research team
Perform statistical and economic research using traditional financial and alternative data to develop new alpha signals.
Successful researchers manage, in collaboration with supervising portfolio manager, all aspects of the research process including data ingestion and processing, data analysis, methodology selection, implementation and testing, prototyping, and performance evaluation.
Engage in building, training and fine-tuning machine learning architectures for cross-sectional or time-series
Learn how to use the appropriate model for the problem at hand.
Construct economically nuanced features from raw data and adjust or develop new frameworks to evaluate their effectiveness.
Engage with most recent academic and practitioner literature in the field.
Occasionally, conduct research on various aspects of the implementation of investment strategies such as trading cost models, risk models, optimization, and portfolio construction
Add features to proprietary research system to implement new research ideas