Data Scientist / Researcher - Systematic Fund | UAE

Durlston Partners

City of London

7 months ago

Applications closed

Related Jobs

View all jobs

Genomic Data Scientist in Rare Disease (we have office locations in Cambridge, Leeds & London)

Senior RF Data Scientist / Research Engineer

Capacity Planning Data Scientist

Data Scientist

Senior Data Scientist

Business Data Analyst

We are partnered with an elite systematic investment fund in the UAE seeking Data Scientists and Data Researchers with a strong interest in AI and Finance to join their growing team. This role sits at the intersection of quantitative research and data science, with a focus on advancing systematic investing through innovative data solutions.

Key Responsibilities:

Data Ingestion & Cleansing: Develop pipelines to integrate and clean large, complex datasets (commodities, equities, alternative data).
Data Analysis: Apply statistical and machine learning techniques to uncover actionable insights for investment strategies.
Data Infrastructure: Maintain and optimise automated systems for data collection, storage, and retrieval to support the research process.
Collaborate with researchers, engineers, and finance experts to enhance model performance and research workflows.
Apply domain expertise to improve the financial accuracy and relevance of AI-driven outputs.

Key Requirements:

Bachelor’s degree in Finance, Computer Science, or a related discipline
2+ years of experience in finance, data science, or a closely related field
Strong understanding of macroeconomics, financial markets, and investment principles
Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy
Strong analytical skills with the ability to design efficient data pipelines and workflows
Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders

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

Location:

UAE - Relocation support provided

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Apr 9, 2026

Products

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Mar 24, 2026

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

Feb 10, 2026

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.