Global Stock Selection Research VP/ED – Technical Signals

AQR•Greenwich, CT

8d•$255,000 - $275,000

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. About The Team 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. The team is tasked with building all the firm’s alpha models used in equity products. Your Role AQR is seeking a talented Researcher to report to the co-Head of Global Stock Selection and collaborate closely on key projects and new initiatives. 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. This role will involve collaboration with other researchers, portfolio managers, risk managers and traders to develop new and improve current investment strategies. Your responsibilities may include, but are not limited to: Perform statistical and economic research using alternative and traditional financial 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. Build alpha-generating signals from scratch, including cleaning and processing large-scale raw data with effective programming tools, feature-engineering based on economic and mathematical intuitions, building, training and fine-tuning machine learning architectures for cross-sectional or time-series prediction, and systematically evaluating the effectiveness of the signals. Engage with most recent academic and practitioner literature in the field. 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

Requirements

B.S. degree from a top institution in computer science, engineering, mathematics, statistics, operations research, physics or another quantitative discipline. Advanced degrees preferred.
7+ years’ experience working in a data driven research environment with an alpha focus
Proficiency in Python required
Ability to manipulate large financial data sets for empirical research and handle complex systems.
Strong quantitative skills with demonstrated understanding of mathematics, probability and data science.
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

Experience in quantitative research at a top asset manager or hedge fund preferred
Experience with technical/market data based alpha sources at medium and long forecast horizons preferred

Responsibilities

Perform statistical and economic research using alternative and traditional financial data to develop new alpha signals.
Build alpha-generating signals from scratch, including cleaning and processing large-scale raw data with effective programming tools, feature-engineering based on economic and mathematical intuitions, building, training and fine-tuning machine learning architectures for cross-sectional or time-series prediction, and systematically evaluating the effectiveness of the signals.
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