Senior Quant Analyst / Research Scientist (Contract) Location: London (cross-Atlantic collaboration) Contract: 12 months (strong potential for extension/perm role) Overview A leading global asset management firm is seeking a senior buy-side Quant Analyst / Research Scientist to support its Fund-of-Funds portfolio within a Front Office–aligned Advanced Analytics function. This is a high-impact contract mandate focused on: Hybrid annuity asset allocation modelling Cashflow forecasting Quadratic and convex optimisation Portfolio construction frameworks Python-based prototyping and deployment The role sits at the intersection of quant research, front office portfolio management, and technology deployment, contributing directly to investment strategy and production-ready solutions. You will work within a high-profile Applied R&D environment supporting Active Equities, Fixed Income, Risk Management, Corporate Finance and broader multi-asset strategies. Core Mandate The primary objective is to design and prototype quantitative models that support: Hybrid and annuity-style asset allocation Fund-of-funds portfolio construction Cashflow forecasting and liability-style modelling Constrained and quadratic optimisation problems This is fundamentally a modelling-first mandate, requiring deep applied mathematics capability and hands-on implementation in Python. AI/ML exposure is desirable but secondary — the role is not a pure AI engineering position. Key Responsibilities Develop and implement quantitative models for hybrid annuity asset allocation Solve quadratic, convex, and mixed-integer optimisation problems Apply portfolio construction standards including: Markowitz / Modern Portfolio Theory Black-Litterman Factor models Forecast portfolio cashflows and support annuity-style allocation structures Build robust prototype frameworks in Python Create comprehensive evaluation frameworks including: Out-of-sample validation Simulation Back-testing Analyse model performance and robustness Collaborate directly with front office PMs on assumptions and outputs Engage with quant research and AI teams to industrialise modelling solutions Ensure models are production-ready and operationalised effectively within internal systems Technical Environment Python (production-level proficiency required) Cloud-based research and development platforms: SageMaker Databricks Enterprise data infrastructure: Snowflake Systematic research and quantitative workflows Investment management datasets across multi-asset strategies Required Experience Senior quant experience within buy-side asset management or fund-of-funds environments Strong background in mathematical optimisation and applied modelling Portfolio construction / asset allocation expertise Hands-on Python development capability (not purely supervisory) Experience with equities; fixed income or hybrid portfolio exposure strongly preferred Experience creating model evaluation frameworks (OOS, simulation, back-testing) Experience working with investment management data Ability to read and computationally reproduce academic research Experience translating research outputs into production-grade solutions Comfortable collaborating across international teams (London / US) Desirable Experience Exposure to ML / deep learning architectures Experience integrating AI/ML prototypes into production environments Multi-asset, insurance, or annuity product exposure Experience working alongside Front Office technology teams or PM management tools CFA participation or strong applied financial markets knowledge Graduate degree in a STEM discipline, or equivalent industrial research experience