The Voleon Group

Member of Research Staff, Voleon Securities (New York)

The Voleon Group$120K — $180K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. preferred in a relevant field with advanced statistical and machine learning knowledge.
  • Experience with optimal control, deep RL, deep learning, or causal inference is a plus.
  • Proven mathematical abilities demonstrated through publications or advanced coursework.
  • Interest in software development and coding proficiency in Python.
  • Capability to address large-scale computing challenges.
  • Desire to thrive in a fast-paced business environment.
  • Interest in finance applications, although direct finance experience isn't necessary.

Responsibilities

  • Develop innovative strategies to enhance Voleon's trading models.
  • Analyze new datasets for predictive performance evaluation.
  • Create, test, and deploy new predictive models.
  • Conduct experiments to improve model simulations and assess performance in real trading.
  • Collaborate with research and engineering teams for project advancement.
  • Stay updated on the latest research trends for potential application in projects.

Benefits

  • Collaborative work environment with a focus on creativity and collegiality.
  • Potential to engage deeply with cutting-edge research in machine learning.
  • Opportunity to impact real-world financial market predictions directly.
  • Support for continuous learning and professional development in a growing firm.
Full Job Description
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.

Responsibilities
  • Develop a rich understanding of Voleon's challenges and methodologies and propose research innovations and experiments to build, maintain and optimize the models that govern our trading strategy
  • Prepare and analyze new datasets to assess their predictive efficacy
  • Develop, validate, and implement new models into production
  • Design and conduct experiments to improve simulations and evaluate the success of new models in a live environment
  • 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 academic research to identify novel approaches to explore for application to our domain


Requirements
  • Background in modern statistical methods and machine learning with a track record as an applied researcher, preferably with experience in at least one of the following: optimal control, deep RL, deep learning, and causal inference
  • Hands-on experience building successful liquidity providing strategies across asset classes preferred but not required
  • 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)
  • Ability to solve large-scale computing problems
  • 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
  • Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred


"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.

About The Voleon Group

The Voleon Group is a quantitative investment management firm that uses advanced mathematical and statistical techniques to identify and exploit market inefficiencies. The company was founded in 2007 by Michael Kharitonov and Jon McAuliffe and is based in San Francisco, California. Voleon's investment strategies are based on machine learning and artificial intelligence, and the company has a team of over 200 researchers and engineers working to develop and improve its algorithms. Voleon manages several funds, including a long/short equity fund and a futures fund, and has a strong track record of performance. The company is known for its rigorous approach to research and its commitment to transparency and ethical behavior.
Learn more about The Voleon Group
Size
200 employees
Industry
Founded
2007

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