Junior Quant - Portfolio Analytics

About Man Systematic 

Man Systematic — formed by Man AHL and Man Numeric — is one of the largest and most diversified systematic investment platforms in the world, managing in the region of $150 billion across hedge funds, long-only programmes, total return strategies, and bespoke Solutions mandates.  

For over  35 years, AHL and Numeric have been blending techniques from machine learning, statistics, and physics with world-class engineering to stay ahead of the curve — research-driven, technology-native, and obsessive about the integrity of the investment process from data to execution. It's a place where smart, curious people from all kinds of backgrounds come together to solve genuinely hard problems and see their ideas make a real impact in financial markets. 

The combined platform offers exposure to virtually every systematic style and asset class on the market — including trend & quant macro, vol, credit, EMN & stat arb, alpha capture, risk premia, beta+, and target risk. More at www.man.com/ahl  and  www.man.com/numeric. 

The Team: Systematic Portfolio Analytics 

Systematic Portfolio Analytics has been a core function within Man AHL for the past four years and is now expanding its mandate to cover the entirety of Man Systematic — both AHL and Numeric. This is not a new team finding its feet; it is a proven, established function with a strong track record inside AHL, now scaling up to deliver across one of the largest systematic platforms in the world. 

Our mandate is to deliver quantifiable, transparent, and actionable insights across the entire systematic estate — from individual signals all the way through to fund-level outcomes. We are an integral part of the decision-making process, helping determine where research effort and risk capital should be allocated, and our work is a fundamental node in the feedback loop between research, portfolio management, and the business. 

Joining now means joining at a genuinely exciting inflection point: a battle-tested team, a proven playbook, and a step-change in scope — with the opportunity to help shape how Portfolio Analytics is built out across Numeric and the combined platform. 

What We're Looking For 

We care more about raw ability, curiosity and drive than years of experience. The ideal candidate is someone who: 

• Is a genuine self-starter — comfortable defining their own problems and running with them
• Has extremely high attention to detail — the kind of person who notices the thing nobody else notices
• Is entrepreneurial — sees gaps and fills them, without needing to be asked
• Is constantly curious about the "why" — never satisfied with a surface-level answer
• Loves solving problems — and gets energy from hard, ambiguous ones
• Is excited by AI and modern tooling, and proactive about integrating it into their workflow 

You will: 

• Aggressively adopt AI and cutting-edge tooling to multiply your own output and the team's output
• Work with — and make sense of — vast amounts of data across both AHL and Numeric
• Develop analytics, KPIs and metrics that turn raw data into intelligence
• Carry out research aimed at uncovering non-obvious insights about our strategies, signals and portfolios
• Write code, build reporting mechanisms, and create tools that PMs and researchers actually use
• Rapidly build a deep understanding of the systematic estate, and leverage that knowledge to generate cross-functional insights and synergies between AHL and Numeric
• Partner closely with PMs, researchers, technologists and traders on both sides of the Atlantic 

Technical Skills 

Essential 

• Strong analytical & statistical skills — and able to translate them into pragmatic, real-world solutions
• Comfortable with large datasets and risk management techniques
• Expertise in a high-level programming language (ideally Python) and its scientific stack (NumPy / SciPy / Pandas or similar) 

Advantageous 

• Familiarity with modern AI tooling (LLMs, agentic workflows, Claude Code / Codex CLI)
• Exposure in key areas on the sell-side, e.g. Trading, Risk, QIS, Financial Engineering, Strats / Quants, Portfolio Management, Electronic / Systematic Trading
• Experience analysing or managing complex risk
• Linux, SQL / Oracle, KDB+ 

Personal Attributes 

• Strong academic record from a leading university, with a degree containing high mathematical, statistical and computing content (e.g. Mathematics, Computer Science, Engineering, Economics, Physics, or Statistics)
• Keen interest in financial markets
• Hands-on attitude; willing to get involved with technology and projects across the firm
• Intellectually robust, with a positive attitude to ambiguity and hard problems
• Self-organised, able to manage time effectively across multiple competing priorities
• Strong interpersonal skills; able to build close working relationships with quantitative researchers, technologists, traders and senior business people alike
• Confident communicator; able to argue a point concisely and deal positively with conflicting views
• Strong sense of integrity