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Salary
$275k – $300k per year
Location
Remote/Hybrid (Berkeley, New York, United States)
Seniority
Staff · 10+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
The Voleon Group is a premier quantitative investment management firm headquartered in Berkeley, California, that specializes in machine learning-driven trading strategies. Founded in 2007 by scientists Michael Kharitonov and Jon McAuliffe, the hedge fund combines advanced data science, statistical modeling, and computational AI to forecast financial markets and execute systematic algorithmic trades.

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future.

Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.

As a Senior Member of Research Staff, you will work at the forefront of modern statistical machine learning leading key projects focused on enduring challenges of financial market prediction and portfolio optimization. Your research colleagues 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 by two leading scientists Voleon supports a culture of curiosity and creativity. We do not silo our teams, and you will enjoy a healthy work-life balance while tackling hard problems.

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. Your team will work with a complex and diverse array of datasets to implement and rapidly iterate on predictive models. Despite the complexity of these problems, market returns provide immediate and unambiguous outcome data for measuring success.

Your team won’t just conduct research, they’ll apply it on a daily basis across the entire life cycle of applied research problems. Your work will span from overseeing projects focused on basic research to productizing solutions and validating their efficacy in live trading. This role is a means to make a difference: you will help direct billions of dollars in trades daily while making an enduring impact on our field.

*** Relocation and work visa eligibility for qualified candidates***

Responsibilities

  • Demonstrate strategic vision and perspective to oversee work that affects one or more complex systems and mission-critical areas

  • Complete large scope, highly complex projects resulting in noteworthy improvements to product performance and risk management

  • Develop a rich understanding of Voleon’s domain and methodologies

  • 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

  • Build collaborative relationships cross-functionally and with key contacts outside own area of expertise, with the potential to serve as an external spokesperson for the organization

  • Communicate and collaborate effectively with key stakeholders at each stage, facilitating meaningful discussions around complex issues and driving progress towards tangible outcomes

  • Mentor other researchers and provide technical guidance, coaching, and feedback

  • Keep up to date on the latest academic research to identify novel approaches to explore for application to our domain

  • Contribute to Voleon's efforts to recruit exceptional talent

Requirements

  • 5-10+ years of related experience directing key research projects and mentoring colleagues

  • Capability to run multiple projects simultaneously, exercising judgment in the methods, techniques, and evaluation criteria for determining results

  • Ability to make well-reasoned design decisions, identifying and proactively potential issues, tradeoffs, risks, and the appropriate level of abstraction

  • Proven success solving large-scale computing problems

  • Expertise in modern statistical methods and machine learning with a track record as an applied researcher

  • Evidence of strong mathematical abilities

  • Strong skills in software development techniques and production level coding (Python and/or R preferred)

  • Effective at communicating complex technical issues simply and transparently, including writing insightful documentation

  • Ability to influence without requiring formal authority, with a proven track record of influence beyond your team

  • Interest in financial applications is essential, but prior finance industry experience is not a prerequisite

  • 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.

Equal Opportunity Employer

The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

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