Member of Research Staff

About the role

You will own the end to end lifecycle of research projects that directly influence live trading systems at Voleon. This role requires you to translate ambiguous financial questions into rigorous machine learning formulations and to iterate on them until they produce robust, production grade results. You will work alongside world class researchers to design experiments that stress test the limits of existing models and uncover new edges in market prediction. Your contributions will shape how billions of dollars are allocated within our investment strategies on a daily basis. You are expected to communicate your findings clearly to both technical and non technical stakeholders, ensuring that insights are actionable. Ultimately, your work will determine which ideas graduate from exploration to execution in our production environment.

Key facts

What you'll do

Investigate novel predictive signals by preparing and analyzing new datasets to assess their efficacy within our investment frameworks.

Design and conduct experiments that improve simulations and evaluate the success of new models in live trading environments with rigorous scientific standards.

Develop, validate, and implement new models into production systems, ensuring they meet performance, reliability, and risk constraints.

Build a rich understanding of Voleon's multifaceted challenges and methodologies to propose research innovations and experiments that optimize our models.

Collaborate effectively with other Members of Research Staff and Software Engineers at every stage of the project lifecycle, driving progress toward tangible, measurable outcomes.

Solve large scale computing problems by leveraging advanced software development techniques and infrastructure to handle complex and diverse datasets.

Keep up to date with the latest academic research to identify novel approaches that can be applied to financial market prediction and portfolio optimization.

Communicate results clearly and persuasively to both technical and non technical audiences, translating complex findings into actionable strategies.

Maintain intellectual curiosity and rigor while working on problems that span from basic research to productization and live validation.

Help direct billions of dollars in trades daily by ensuring that models are robust, well validated, and aligned with business objectives.

Contribute to a culture of curiosity and creativity by sharing ideas openly, participating in regular research discussions, and staying current with advances in the field.

Support the broader mission of applying AI and machine learning to real world problems with the same discipline and integrity that defines Voleon's research legacy.

Requirements

You possess a strong background in modern statistical methods and machine learning, with a documented track record as an applied researcher in relevant domains.

You have evidence of strong mathematical abilities, demonstrated through publication records, graduate coursework, or competition placement that reflects analytical depth.

You have a keen interest in software development techniques and are willing to write production level code, with Python and or R being your preferred languages.

You are capable of solving large scale computing problems, designing systems that are efficient, scalable, and maintainable.

You show eagerness to work in collaborative and diverse teams, valuing different perspectives and contributing constructively to shared goals.

A strong interest in financial applications is essential, although prior finance industry experience is not a prerequisite for success in this role.

Ph.D. level coursework is required, and holding a Ph.D. degree in a relevant field is preferred as proof of sustained research excellence.

You are prepared to engage in rigorous scientific inquiry, adhering to the highest standards of reproducibility, validation, and ethical responsibility in model development.

Nice to have

Preferred candidates will have experience working at the intersection of machine learning and finance, with a demonstrated ability to turn theoretical ideas into practical solutions.

Familiarity with the challenges of financial market prediction, including issues related to non stationarity, noise, and sparse signal, will help you navigate the domain more effectively.

Experience with production grade software engineering, including version control, testing, and deployment pipelines, will be viewed as a significant advantage.

Knowledge of modern data stacks and scalable computing frameworks will support your ability to handle complex and diverse datasets at Voleon's scale.

An interest in communicating research results to both technical and non technical stakeholders is highly valued, as this role requires translating advanced concepts into actionable strategies.

Practical notes

This is a full time position based in London.

The role requires availability during standard working hours as defined by the company's operational needs.

Candidates must be eligible to work in the United Kingdom without sponsorship, or must already hold the right to work under UK immigration rules.

Relocation support may be considered for qualified candidates where applicable, subject to internal policies and constraints.

"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 https://voleon.com/referrals/ to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program https://voleon.com/assets/Voleon-Referral-Bonus-Program.pdf.

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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