Quantitative Researcher - AI/ML at Man Group

Shanghai, Shanghai, China -

Full Time

Start Date

Immediate

Expiry Date

24 Sep, 26

Salary

0.0

Posted On

26 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Deep Learning, Quantitative Research, Natural Language Processing, Large Language Models, Probabilistic Modeling, Optimization, Reinforcement Learning, Statistical Analysis, Feature Engineering, Cloud Computing, GPU Computing, Portfolio Optimization, Backtesting, Python, Financial Modeling

Industry

Investment Management

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 $228.7 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 At Man Group, we respect your privacy and we are committed to protecting and safeguarding your Personal Data. We have developed policies and processes which are designed to provide for the security and integrity of your Personal Data. We are committed to Processing your Personal Data fairly and lawfully, and being open and transparent about such Processing. For further information on how we process your data, please see the privacy notice for applicants here * As at 31 March 2026 ML/AI: Key competencies Advanced degree in Computer Science, Statistics, Mathematics, Finance/Economics or related quantitative field from a top-tier institution Passion in investment research with strong intuition and the ability to think-out-of-the-box Background in core ML theory: optimization, probabilistic modeling, deep learning architectures (transformers, diffusion models, etc.) Strong publication record or thesis work in ML/AI (conference papers at NeurIPS, ICML, ICLR, ACL etc. are preferred); hands-on experience in fine-tuning large-scale foundation models Experience with cloud environments and multi-machine CPU/GPU setups Ability to communicate complex ideas clearly, strong collaboration skills to partner with other teams to implement ideas into products Prior experience in the investment field is a plus but not required What you will be doing Develop and improve AI-driven quantitative investment strategies in financial markets within the dedicated China research team. Support all strategies from alpha generation through to trade execution and implementation, working closely with other team members to design, build, and enhance strategies using cutting-edge machine learning and AI techniques. Core responsibilities include: Alpha Generation & Idea Discovery: Leverage large language models (LLMs), NLP, and alternative data pipelines to identify novel investment signals and innovative data sources Data Gathering & Refinement: Apply AI-powered data processing and feature engineering techniques to gather, clean, and structure complex datasets for modeling at scale. Modeling & Statistical Analysis: Design and implement deep learning, reinforcement learning, and statistical ML models to build, backtest, and refine various quantitative models. Interpretation & Presentation: Translate complex AI model outputs into actionable investment insights, ensuring model interpretability and explainability when communicating results to stakeholders. Implementation Research: Conduct research on AI-enhanced implementation aspects of investment strategies, including ML-based trading cost models, learned risk models, AI-assisted portfolio optimization, and dynamic portfolio construction. 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 TalentAcquisition@man.com.

Responsibilities

Develop and improve AI-driven quantitative investment strategies, focusing on alpha generation and trade execution. Responsibilities include leveraging LLMs for signal discovery and designing deep learning models for portfolio optimization.