Man Group

FinTech

QuantitativeResearchIntern

$100–150k ~AI est. Hong Kong, Hong Kong INTERNSHIP
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Quantitative Research Intern at Man Group. Skills: Quantitative research, Machine learning, Statistical analysis. Research time-series methods. Research advanced statistical techniques”

What You'll Achieve.

Iterate towards deployable outcomes

Industry & Context.

FinTech
Problems you'll solve

Rigorous backtesting; Diagnosing overfitting; Questioning assumptions

What They're Looking For.

Must Have

Bachelor's in computer science, Bachelor's in statistics, Bachelor's in machine learning, Bachelor's in signal processing, Bachelor's in optimization, Bachelor's in mathematics, Bachelor's in physics, Master's in computer science, Master's in statistics, Master's in machine learning, Master's in signal processing, Master's in optimization, Master's in mathematics, Master's in physics, PhD in computer science, PhD in statistics, PhD in machine learning, PhD in signal processing, PhD in optimization, PhD in mathematics, PhD in physics, Proficiency in Python, Solid understanding of data structures, Solid understanding of algorithmic complexity, Solid understanding of numerical libraries, Demonstrated ability to conduct research, Ability to communicate complex results

Nice to Have

PhD preferred, Specific ML framework experience, Cloud platform certs

What You'll Do.

Research time-series methods

Research advanced statistical techniques

Research machine learning models

Extract predictive value from datasets

Analyze noisy datasets

Identify systematic trading opportunities

Develop statistical tools

Develop ML-based tools

Solve data-related problems

Prototype signal variants

Document work cleanly

How You'll Work.

Team & Collaboration

Day-to-day mentorship; Core supervision; High-level exposure; Discuss research results; Present research results; Incorporate feedback

Communication Scope

Communicate complex results; Present research results

Process & Methodology

End-to-end research project ownership

Full Job Description

About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com * As at 31 December 2025 Location: Hong Kong SAR Duration: 3–4 months, starting 2026 Eligibility: Final year students (Bachelor's, Master's, or PhD) The Team Join the Specialist Equities team, a small and collaborative systematic equity research group focused on developing medium-frequency statistical arbitrage alpha signals. You will receive day-to-day mentorship from a quantitative researcher in Hong Kong, with core supervision and high-level exposure to portfolio managers and senior management in London. Position Overview You will own a research project end-to-end, taking a disciplined scientific approach to form hypotheses, construct signals, and iterate towards deployable outcomes. The project scope is defined on our side and will be closely tailored to your specific background and strengths once we've met you. During the internship, you will: Research time-series methods, advanced statistical techniques, and machine learning models to extract predictive value from complex datasets. Analyze large, noisy, real-world data sets to identify systematic trading

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