Quant Researcher

Man Group•Boston, MA

5d•$110,000 - $130,000

About The Position

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. The Systematic Portfolio Analytics team 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 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. The role involves aggressively adopting AI and cutting-edge tooling to multiply individual and team output, working with vast amounts of data, developing analytics, KPIs, and metrics, carrying out research to uncover non-obvious insights, writing code, building reporting mechanisms, and creating tools for PMs and researchers. The role also requires rapidly building a deep understanding of the systematic estate and leveraging that knowledge to generate cross-functional insights and synergies between AHL and Numeric.

Requirements

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)
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-organized, 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

Nice To Haves

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 analyzing or managing complex risk
Linux, SQL / Oracle, KDB+

Responsibilities

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