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Member of Research Staff - Machine Learning & Financial Markets

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AI Summary

Develop and optimize statistical machine learning models for financial market prediction and portfolio optimization. Collaborate with research and engineering teams to implement predictive models into live trading environments. Requires a Ph.D. level background in machine learning, strong mathematical abilities, and proficiency in Python or R.

Key Highlights
Work at the forefront of modern statistical machine learning applied to finance
Direct billions of dollars in daily trades through model development
Collaborative environment with internationally recognized AI/ML experts
Key Responsibilities
Propose research innovations and experiments to build, maintain, and optimize investment strategy models
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 model success in live environments
Communicate and collaborate with research staff and software engineers to drive progress
Keep up to date on the latest academic research to identify novel approaches
Technical Skills Required
Machine Learning Statistical Methods Python
Benefits & Perks
Highly competitive compensation and benefits packages
Daily catered lunches
Relocation and work visa eligibility for qualified candidates
Nice to Have
Ph.D. degree in a relevant field
Prior finance industry experience

Job Description


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 Member of Research Staff, you will work at the forefront of modern statistical machine learning. 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 in 2007 by two leading scientists (see management bios), 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. 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

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 investment 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

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 and/or R preferred)

Ability to solve large-scale computing problems

Eagerness to work in collaborative and diverse teams

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

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