Member of Research Staff (London) - Class of 2026 at The Voleon Group

London, England, United Kingdom

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Not SpecifiedCompensation

Entry Level & New GradExperience Level

Full TimeJob Type

UnknownVisa

Finance, Investment Management, TechnologyIndustries

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

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

Skills

Key technologies and capabilities for this role

AIMachine LearningStatistical Machine LearningPredictive ModelingPortfolio OptimizationFinancial MarketsData Analysis

Questions & Answers

Common questions about this position

What is the location for this Member of Research Staff position?

The position is based in London.

Does the company offer relocation or visa support?

Yes, relocation and work visa eligibility are offered for qualified candidates.

What are the main responsibilities for this role?

Responsibilities include developing research innovations and experiments for investment models, preparing and analyzing datasets, developing and implementing models into production, designing experiments, collaborating with teams, and staying current on academic research.

What is the company culture like at Voleon?

Voleon supports a culture of curiosity and creativity, does not silo teams, promotes a healthy work-life balance, and features colleagues who are internationally recognized experts in AI/ML with hundreds of academic publications.

What kind of background makes a strong candidate for this role?

Candidates with years of academic training in statistical machine learning, experience applying research across the full lifecycle from basic research to production, and the ability to work with complex financial datasets on market prediction and portfolio optimization will stand out.

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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