[Remote] Member of Research Staff, Voleon Securities at The Voleon Group

New York, New York, United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

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

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

Skills

The Voleon Group

Investment management using machine learning algorithms

About The Voleon Group

Voleon focuses on investment management by utilizing machine learning to analyze financial market trends. The firm uses advanced statistical models to process large datasets and identify patterns that inform investment decisions, setting it apart from traditional methods that rely on human intuition. Voleon serves institutional clients and operates on a performance-based fee structure, aligning its interests with those of its clients. The company's goal is to provide data-driven insights that optimize investment returns while adapting to changing market conditions.

Berkeley, CaliforniaHeadquarters

2007Year Founded

VENTURE_UNKNOWNCompany Stage

Quantitative Finance, Financial ServicesIndustries

51-200Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Paid Vacation

Paid Sick Leave

401(k) Retirement Plan

401(k) Company Match

Risks

Competition from other quantitative hedge funds may erode Voleon's market share.

Regulatory scrutiny on AI use in finance could increase compliance costs for Voleon.

Data quality issues could lead to inaccurate predictions and financial losses for Voleon.

Differentiation

Voleon uses machine learning for data-driven financial market predictions.

The firm serves institutional clients with a focus on scalability and risk management.

Voleon's academic approach emphasizes intellectual rigor and continuous learning.

Upsides

Increased interest in ESG investing offers new opportunities for Voleon's models.

Alternative data sources enhance predictive models for quantitative hedge funds like Voleon.

Cloud computing enables efficient scaling of Voleon's data processing capabilities.

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