Location
London

Hours
Full Time

Salary
Competitive salary package

About the Role
Man Group is a global alternative investment management firm focused on delivering outperformance for sophisticated clients through Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, we manage a diverse range of investment strategies across public and private markets with a significant focus on alternatives. Headquartered in London, we manage $228.7 billion and operate globally.

Within Man Group, the Man Systematic platform—formed by Man AHL and Man Numeric—is one of the largest and most diversified systematic investment platforms worldwide, managing approximately $150 billion in funds and strategies. The Systematic Portfolio Analytics team is a proven, established function within Man AHL, now expanding to cover the entire Man Systematic platform. The team delivers quantifiable, transparent, and actionable insights across the systematic estate, playing a key role in decision-making and the feedback loop between research, portfolio management, and business.

As a Junior Quant in Portfolio Analytics, you will aggressively adopt AI and cutting-edge tooling to enhance both your own and the team's output. You will work with vast datasets across AHL and Numeric, develop analytics, KPIs, and metrics that transform raw data into intelligence, and conduct research to uncover non-obvious insights about strategies, signals, and portfolios. You will write code, build reporting mechanisms, and create tools used by portfolio managers and researchers. This role offers the opportunity to rapidly build a deep understanding of the systematic estate and generate cross-functional insights and synergies.

Experience
No specific years of experience required; emphasis is on raw ability, curiosity, and drive. Experience with large datasets, risk management techniques, and programming (ideally Python and its scientific stack) is essential. Familiarity with modern AI tooling and exposure to sell-side areas such as Trading, Risk, QIS, Financial Engineering, or Systematic Trading is advantageous.

About you
- Genuine self-starter comfortable defining and pursuing problems independently
- Extremely high attention to detail
- Entrepreneurial mindset, proactive in identifying and filling gaps
- Constantly curious and eager to understand the "why" behind things
- Passionate about solving hard, ambiguous problems
- Excited by AI and modern tooling
- Strong interpersonal skills and confident communicator
- Self-organised with the ability to manage multiple priorities effectively
- Positive attitude towards ambiguity and complex challenges
- Keen interest in financial markets

Qualifications
Strong academic record from a leading university with a degree containing high mathematical, statistical, and computing content such as Mathematics, Computer Science, Engineering, Economics, Physics, or Statistics.