We are looking to add an experienced and creative causal inference researcher to our growing ML research group. We welcome researchers with both strong theoretical foundations and experience applying causal inference methods in industrial settings. Financial applications of causal inference are challenging and demand new methods that go beyond the academic state-of-the-art; it is critical candidates have a deep understanding of the field to draw inspiration for new methodology.
This is a chance to join the initial buildout of a fully modern securities business rooted in the frontier of AI/ML and statistics. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals.
As a Member of Research Staff, you will work at the forefront of modern statistical machine learning. Your research colleagues across Voleon have collectively published hundreds of academic articles in top-tier venues on machine learning, systems, and theory, and we meet regularly to stay current on the latest academic research and share ideas. Founded in 2007 by two leading scientists, Voleon supports a culture of curiosity, collegiality, and creativity.
Your work will focus on financial market prediction and portfolio optimization. The behavior of financial markets is noisy and violates a number of classical statistical assumptions, and we've spent over a decade pioneering scientific advances in the application of machine learning techniques to this domain. You will work with a complex and diverse array of datasets to implement and iterate on predictive models. Predicting financial markets is an enduringly hard problem, but results are immediate and unambiguous.
Years of academic training has prepared you for this moment. You won't just conduct research, you'll apply it on a daily basis, working with a team across the entire life cycle of applied research problems. Your work will span from basic research to productizing solutions and validating their efficacy in live trading.
Relocation and work visa eligibility for qualified candidates
Responsibilities- Develop a rich understanding of Voleon's challenges and methodologies and propose causal inference research innovations and experiments to build, maintain and optimize models of the market
- Prepare and analyze new market datasets to gain insight into market microstructure
- Develop, validate, and implement improvements to our models of the market
- Design and conduct synthetic and live trading experiments to sharpen understanding of market behavior
- Communicate and collaborate effectively with other Members of Research Staff and Software Engineers at each stage, driving progress towards tangible outcomes
- Keep up to date on the latest causal inference academic research to identify novel approaches to explore for application to our domain
Requirements- Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred
- Background in causal inference and statistics with a strong track record of publishing causal inference papers in top tier journals and conferences
- Evidence of strong mathematical abilities (e.g., publication record, graduate coursework, or competition placement)
- Interest in software development techniques and willingness to write production-level code (Python)
- Eagerness to work in a fast paced and growing business
- Interest in financial applications is essential, but prior finance industry experience is not a pre-requisite
"Friends of Voleon" Candidate Referral Program If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program.
