Job Specifications
A leading investment team in The UAE is seeking a highly skilled Quantitative Researcher to play a key role in advancing systematic research and decision-making systems. This position blends traditional portfolio research with cutting-edge AI applications, offering the opportunity to shape and deliver production-grade solutions that directly impact investment evaluation and analytics.
The successful candidate will act as the team's practical AI lead, owning the knowledge graph, GNN/graph-embedding models, and LLM/NLP extraction + RAG systems that power investment workflows. Alongside this, the role will involve designing research processes, monitoring portfolios, and contributing to systematic fund-of-funds strategies.
Key Responsibilities
Systematic Research & Investment Support:
Conduct research to design and enhance systems that identify and evaluate opportunities across external managers and systematic strategies relevant to fund-of-funds portfolios.
Apply quantitative and fundamental techniques to assess performance drivers, risk decomposition, factor/style exposures, and persistence.
Develop and maintain models for investment decision-making, including manager screening, portfolio construction, monitoring, and scenario/sensitivity analysis.
Monitor portfolios of hedge funds and traditional funds, designing and recommending overlay strategies or hedges where appropriate.
Produce detailed reports and presentations for senior stakeholders, synthesizing manager interviews into clear, well-documented insights.
AI & Data Systems:
Design and maintain domain ontologies, building and operating knowledge graphs (e.g., Neo4j) with versioning, provenance, consent/visibility controls, and schema evolution.
Build NLP/LLM pipelines for information extraction across diverse document sources; develop hybrid retrieval systems with evaluators for relevance, faithfulness, and citation.
Train embeddings for nodes and relations, prototype GNNs and advanced hypergraph/VGAE models, and run prediction tasks to enrich the knowledge graph.
Collaborate with researchers, portfolio managers, and technology teams to ensure solutions are integrated, scalable, and optimized for investment workflows.
Create and maintain comprehensive documentation, providing knowledge transfer and training to ensure best practices across teams
Preferred Qualifications:
Experience in financial services (e.g., brokerage, asset management, or banking) or a strong macroeconomic research background
Familiarity with machine learning, NLP, and large language models (LLMs)
Knowledge of various datasets (e.g., earnings, filings, credit card, CCTV)
Master's degree in a relevant field is a plus
About the Company
Durlston Partners began recruiting for the world's best Hedge Funds in 2010 and we have grown our business to deliver best-in-class talent to companies in Tech, Quant Finance, Portfolio Management, Data Science & Digital Assets.
Our team operates from our offices in London, New York and Dubai. Led by 5 Partners, we have achieved organic growth and self-funded success without external investment.
Our clients include leading hedge funds, banks, family offices, and AI / Machine Learning firms across global financial hubs such...
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