Quantitative Research Intern – Specialist Equities

Reposted 4 Days Ago
Be an Early Applicant
Hiring Remotely in Hong Kong
Remote
Internship
Financial Services
The Role
The Quantitative Research Intern will conduct research on statistical methods and ML models to analyze complex datasets for trading opportunities, with mentorship and exposure to senior team members.
Summary Generated by Built In

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 opportunities.
  • Help develop statistical and ML-based tools and techniques to solve complex data-related problems throughout the research process.
Typical Day
  • Your primary focus throughout the day will be on researching new statistical techniques, exploring datasets, and prototyping signal variants.
  • Apply critical thinking at every step—rigorously backtesting ideas, diagnosing overfitting, and questioning your own assumptions.
  • Discuss and present research results with your immediate team, portfolio managers, and senior management, actively incorporating their feedback.
  • Document your work cleanly and clearly so colleagues can easily build upon your findings.
Required Qualifications
  • Quantitative Background: Pursuing a Bachelor's, Master's, or PhD in computer science, statistics, machine learning, signal processing, optimization, mathematics, physics, or a related STEM subject.
  • Research Excellence: Demonstrated ability to conduct high-quality, in-depth, and rigorous research on real-world data, along with the ability to communicate complex results clearly to both technical peers and senior stakeholders.
  • Programming Proficiency: Strong proficiency in Python, with a solid understanding of data structures, algorithmic complexity, and numerical libraries (e.g., pandas, numpy).
  • Statistical & ML Knowledge: Strong grasp of probability, statistics, linear algebra, time-series analysis, and machine learning, including the practical ability to recognize and mitigate overfitting.
  • Team Player: Strong communication skills with the ability to work well in a collaborative, high-pace setting, driving projects to completion across accelerated timelines and coordinating with colleagues across multiple regions.
Nice to Have
  • Prior internship in quantitative research or systematic investing.
  • Hands-on experience working with noisy, large-scale financial or alternative datasets.

How to Apply
Apply online with your CV and a short cover note. In your cover note, describe one real research or engineering problem you worked on: what you tried, what worked, what didn't, and what you would do differently.


Inclusion, Work-Life Balance and Benefits at Man Group
You'll thrive in our working environment that champions equality of opportunity. Your unique perspective will contribute to our success, joining a workplace where inclusion is fundamental and deeply embedded in our culture and values. Through our external and internal initiatives, partnerships and programmes, you'll find opportunities to grow, develop your talents, and help foster an inclusive environment for all across our firm and industry. Learn more at www.man.com/diversity.
You'll have opportunities to make a difference through our charitable and global initiatives, while advancing your career through professional development, and with flexible working arrangements available too. Like all our people, you'll receive two annual 'Mankind' days of paid leave for community volunteering.

Our comprehensive benefits package includes competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Depending on your location, you may also enjoy additional benefits such as private medical coverage, discounted gym membership options and pet insurance.

Equal Employment Opportunity Policy

Man Group provides equal employment opportunities to all applicants and all employees without regard to race, color, creed, national origin, ancestry, religion, disability, sex, gender identity and expression, marital status, sexual orientation, military or veteran status, age or any other legally protected category or status in accordance with applicable federal, state and local laws.

Man Group is a Disability Confident Committed employer; if you require help or information on reasonable adjustments as you apply for roles with us, please contact [email protected].


Skills Required

  • Pursuing a Bachelor's, Master's, or PhD in computer science, statistics, machine learning, signal processing, optimization, mathematics, physics, or related STEM subject.
  • Demonstrated ability to conduct high-quality research on real-world data.
  • Strong proficiency in Python and understanding of numerical libraries.
  • Strong grasp of probability, statistics, linear algebra, time-series analysis, and machine learning.
  • Strong communication skills in a collaborative setting.
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The Company
HQ: New York, NY
2,471 Employees
Year Founded: 1783

What We Do

Man Group is a global active investment management firm, which runs $127 billion* of client capital in liquid and private markets, managed by investment specialists based around the world. Headquartered in London, the firm has 15 international offices and operates across multiple jurisdictions. Our business has five specialist investment engines, which represent the range of our capabilities: Man AHL, Man Numeric, Man GLG, Man FRM and Man GPM. These engines house numerous investment teams, working collaboratively within the framework of Man Group, with a high degree of investment autonomy. Each team benefits from the strength and resources of the firm’s single operating platform, enabling their primary focus to be seeking to generate alpha for clients. The teams invest across a diverse range of strategies and asset classes with highly specialised approaches, with long only and alternative strategies run on a discretionary and quantitative basis in single and multi-manager formats. Our clients are at the heart of everything we do and we engage in close dialogue with our investors as strategic partners, to understand their particular needs and constraints. Man Group’s investment teams are empowered and supported by our institutional infrastructure and technology, which aims to facilitate the efficient exposure to markets and effective collaboration across the organisation.

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