Portfolio Construction Quant
Overview
Selby Jennings are partnered with a leading macro fund seeking a highly analytical Portfolio Optimisation Quant to design, build, and enhance the models and tools that drive their capital allocation and portfolio construction processes.
This role bridges quantitative research, risk modelling, and engineering, supporting portfolio managers with robust optimisation analytics and data‑driven insights. The ideal candidate combines strong quantitative ability with practical understanding of real‑world portfolio behaviour, producing solutions that are both mathematically rigorous and operationally scalable.
Responsibilities
- Develop and refine portfolio optimisation frameworks to allocate capital efficiently, balance risk/return trade‑offs, and support portfolio construction across strategies and asset classes.
- Analyse historical and real‑time data to evaluate signals, assess diversification and performance, and build diagnostic tools for risk attribution, forecasting, and portfolio efficiency.
- Build and maintain analytical tools such as optimisation engines, monitoring systems, and dashboards, and partner with engineering teams to deploy scalable, robust models into production.
- Conduct risk and scenario analysis, including stress tests and sensitivity modelling, and work closely with PMs, traders, and quant teams to ensure research aligns with real‑world portfolio decisions.
Required Qualifications
- Degree in a quantitative discipline such as Mathematics, Statistics, Physics, Engineering, Computer Science, or Financial Engineering.
- Strong programming ability in Python (NumPy, pandas, optimisation libraries). Experience with R, MATLAB, SQL, or C++ is a plus.
- Strong understanding of portfolio theory, risk modelling, factor models, and optimisation techniques including mean‑variance, risk budgeting, Black‑Litterman, and convex optimisation.
- Experience in a hedge fund, multi‑manager platform, trading firm, or asset management environment.
Preferred Experience
- Experience with systematic, macro, multi‑strategy, or equities optimisation frameworks.
- Familiarity with scenario analysis, stress testing, capacity modelling, and constraint‑aware optimisation.
- Exposure to multi‑asset portfolios and cross‑asset risk interactions.
- Experience working with engineering teams on deploying models into production systems.
What You'll Gain
- Direct influence over capital allocation and portfolio construction processes.
- Close collaboration with senior portfolio managers, trading teams, and cross‑asset research groups.
- Opportunities to design and improve the optimisation, analytics, and risk infrastructure powering investment decisions.
- A role focused on innovation, scalability, and long‑term quantitative impact.
FAQs
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