Durlston Partners

Data Scientist – Finance Applications – Financial Services Firm – UAE – Up to $180k base

A UAE based financial services firm are looking for a skilled Data Scientist with a passion for finance and AI to join an innovative and expanding team. The selected candidate will be at the forefront of refining large language model (LLM) outputs for financial applications, ensuring that the generated content is accurate.

The base pay for the role ranges up to $180k p.a. and there is an on-site requirement (5 days per week) in their UAE office.

Key Responsibilities:

• Oversee and enhance quality control systems for financial content generated by LLMs
• Develop quality metrics to evaluate the effectiveness and consistency of model-generated content
• Design and implement data pipelines for processing and analysing financial data
• Work closely with cross-functional teams to improve model performance, ensuring higher precision and relevance in financial contexts
• Apply domain expertise to enhance the financial knowledge representation in AI outputs
• Collaborate in an agile, technical environment with data scientists, engineers, and finance experts

Key Requirements:

• Bachelor’s degree in Finance, Computer Science, Economics (Macro), or a related field
• 2+ years of experience in finance, data science, or a related field
• Strong grasp of macroeconomics, financial markets, and investment principles
• Proficiency in Python programming and experience with data manipulation libraries (such as pandas) is a must
• Ability to design and implement efficient data pipelines and processing workflows
• Strong problem-solving and analytical skills
• Ability to articulate complex financial concepts clearly and effectively to both technical and non-technical teams

Preferred Requirements:

• Experience within the financial services industry (e.g., brokerage firms, investment funds, or banking) – in lieu of finance experience, a strong background in macroeconomics is required
• Research or consulting background with a focus on finance
• Knowledge of large language models (LLMs) and AI/ML optimization techniques (fine-tuning and architecture)
• Familiarity with natural language processing (NLP) and machine learning algorithms
• Master’s degree in a relevant field is a plus

What You’ll Get:

• Opportunity to work at the intersection of cutting-edge AI and finance
• A collaborative, tech-driven environment with like-minded professionals
• Room for growth and the chance to shape the future of financial AI applications

About Our Client

Our client is a rapidly expanding buy-side firm specializing in systematic trading across derivatives and cash markets. With a strong emphasis on AI-driven research, they integrate deep learning and reinforcement learning into high-frequency and medium-frequency trading strategies to generate uncorrelated returns for institutional investors.

The Opportunity

Join an elite research team at the forefront of AI-driven quantitative trading. This role focuses on applying state-of-the-art deep learning techniques to options, futures, and structured derivatives markets, with direct exposure to real-time alpha generation, portfolio optimization, and execution strategies. You will develop cutting-edge models for forecasting market dynamics and optimizing trade execution in a systematic, data-driven framework.

Key Responsibilities

• Develop advanced AI/Deep Learning models for predictive signal generation in derivatives markets (volatility surfaces, term structure forecasting, order flow dynamics).
• Apply reinforcement learning to optimize execution strategies, market making, and hedging frameworks.
• Build and refine NLP-based models for extracting signals from alternative datasets (news sentiment, earnings call transcripts, options order flow).
• Enhance systematic options trading strategies (e.g., delta-hedging, volatility arbitrage, statistical arbitrage) using deep learning-based predictive frameworks.
• Deploy and optimize AI models in production with real-time inference and model adaptation to changing market conditions.
• Improve research infrastructure (scalable data pipelines, high-performance backtesting engines, deep learning model training frameworks).
• Collaborate with portfolio managers and execution teams to integrate AI-driven signals into risk-managed trading portfolios.
• Publish internal research on deep learning architectures for financial time series forecasting, reinforcement learning for derivatives trading, and explainability of AI-driven strategies.

Ideal Candidate Profile

• 5+ years of experience in quantitative research, systematic trading, or AI-driven signal development at a top-tier hedge fund, prop firm, or high-frequency trading firm.
• Strong track record of alpha generation in derivatives markets (Sharpe ratio, risk-adjusted returns, and execution efficiency).
• Expertise in AI/Deep Learning frameworks: PyTorch, TensorFlow, JAX, or Hugging Face Transformers.
• Strong programming skills in Python and C++ (for low-latency research and execution).
• Advanced degree (PhD preferred) in AI, Machine Learning, Quantitative Finance, or Computational Sciences.
• Deep knowledge of:
  • Neural networks for time-series forecasting (LSTMs, Transformer models, CNNs for market data).
  • Reinforcement learning for execution optimization (Q-learning, PPO, AlphaZero-style models).
  • Generative models for synthetic data generation (GANs, VAEs, diffusion models).
  • Derivatives pricing models (stochastic volatility, Monte Carlo simulations, local volatility).
  • Market microstructure and high-frequency trading for listed options and futures.
  • Portfolio optimization under liquidity, margin, and regulatory constraints.

Why Join?

• Be a key player in an AI-first quantitative research team, working with top-tier hedge fund PMs and AI researchers.
• Work with exclusive datasets (tick-level options data, alternative data partnerships, deep order book data).
• Access to world-class compute resources for deep learning model training and high-performance AI-driven research.
• Remote-first culture with flexibility to work from anywhere, while engaging with top-tier talent in AI and systematic trading.

A leading investment firm is seeking an experienced Quantitative Analyst to strengthen its investment strategies. With over a decade of incorporating quantitative strategies into their investment process, the firm is looking for someone with more than seven years of experience in quantitative research and financial modelling. In this role, you will collaborate closely with fundamental portfolio managers to develop and refine models that provide data-driven investment insights.

Key Responsibilities

• Develop and maintain quantitative models to support investment decision-making.
• Work closely with fundamental portfolio managers to integrate quantitative insights into investment strategies.
• Analyse financial and market data using statistical, econometric, and AI/ML methodologies to identify trends and opportunities.
• Identify, evaluate, and integrate internal and external data sources.
• Develop scalable tools and processes using R or Python.
• Communicate findings clearly, ensuring transparency in model development, assumptions, and outputs.

Ideal Profile

• 7+ years of experience in quantitative analysis and financial modelling, with expertise in equities and factor investing.
• Master’s degree in Mathematics, Statistics, Computer Science, AI, or a related quantitative or engineering field.
• Proficiency in R/Python for data analysis and model development.
• Strong data science skills, including data cleaning, predictive modelling, and feature engineering.
• Ability to adapt to emerging technologies and integrate AI/ML techniques, including large language models (LLMs).
• Excellent communication and collaboration skills to bridge quantitative research with fundamental investment decision-making.

Please be aware that this role is not eligible for US work permit sponsorship.

About the Company:
Join a leading global macro fund renowned for its cutting-edge technology and innovative approaches. Due to recent success, the fund is expanding its Macro NLP team and is seeking an exceptional NLP Researcher to join their growing team.

The Role:

As an NLP Researcher in Macro Futures, you will apply your expertise in natural language processing to develop and leverage advanced NLP models for proprietary data. You’ll play a pivotal role in a team that leverages cutting-edge AI techniques to tackle complex challenges.

Key Responsibilities:

• Develop and implement NLP techniques for macro futures strategies
• Conduct research and analysis to improve trading models
• Work closely with the Quant Strategy team to apply AI in live trading systems
• Collaborate with other teams to drive innovation and bring new insights into the firm’s trading strategies

Requirements:

• 0-3 years of experience in a quantitative research role, ideally with experience in NLP and Macro Futures
• Strong academic background in Computer Science, Machine Learning, Mathematics, or a related field
• Experience with NLP techniques applied to financial markets is highly desirable
• Familiarity with quantitative research in the Macro Futures space from top-tier buy-side firms.
• Strong programming skills in Python, C++, or similar languages
• Ability to work well within a fast-paced and high-pressure environment

Apply now! If you don’t receive a response within three days, unfortunately, your application has not been successful.

A leading systematic hedge fund, known for its collaborative, research-driven culture, is seeking a Machine Learning Specialist to apply cutting-edge ML techniques to enhance trading strategies and infrastructure.

This is a first-of-its-kind role, where you will act as a subject matter expert in ML, working across asset classes and strategies to develop scalable, high-impact solutions.

With a highly selective team (predominantly Ivy League/Oxbridge grads) and a multi-strat, multi-asset approach, this firm offers a unique opportunity to shape the future of machine learning in systematic finance.

Key Responsibilities:

• Develop & Apply Machine Learning Solutions: Identify opportunities to integrate ML into alpha generation, execution, and risk management.
• Cross-Team Collaboration: Work with quant researchers, traders, and engineers across equities, macro, and volatility strategies.
• End-to-End Implementation: Own the ML research pipeline, from feature extraction to production deployment.
• Stay at the Cutting Edge: Leverage advancements in deep learning, NLP, reinforcement learning, and other AI techniques to enhance systematic trading.
• Multi-Asset Coverage: Apply ML methodologies across equities, vol (rates/converts), commodities, FX, and credit.

Ideal Profile:

• PhD or Master’s in Machine Learning, Computer Science, Applied Mathematics, or a related field, with a strong publication record in top ML/AI conferences.
• First-Principles Thinker: Ability to craft ML solutions tailored to high-performance trading environments.
• Extensive NLP & Feature Engineering Experience: Strong focus on scalable data analysis for signal generation.
• Strong Programming & ML Stack: Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and distributed computing.
• Quantitative Finance Exposure: Preference for candidates with quant experience, not just pure AI/ML backgrounds.

A global proprietary trading firm that has been a major player in traditional financial markets since the early ’90s. Over the past decade, they have expanded aggressively into emerging markets, including Digital Assets, and are now building out a cutting-edge AI-driven trading platform.

Why?

They are launching a new AI division to integrate cutting-edge machine learning, deep learning, and reinforcement learning techniques into their trading strategies. This is a high-impact, greenfield opportunity to shape the firm’s AI capabilities from the ground up, driving innovation in automated trading, predictive modeling, and decision-making systems.

What?

• Lead the research, development, and deployment of AI models for trading and market prediction.
• Architect and build scalable AI/ML infrastructure using Python, TensorFlow/PyTorch, and modern frameworks.
• Work closely with traders, quant researchers, and engineers to optimize execution strategies.
• Develop and implement low-latency, real-time learning systems in production.
• Leverage cloud computing and distributed systems to scale AI workloads.

Where?

Global presence with 10 worldwide offices, including London. This role offers remote flexibility, but a London base is preferred.

How much?

Expect highly competitive compensation, with a base salary of up to £300k + bonus + equity.

Job Title: AI Engineer

About the Role

We are seeking a highly skilled AI Engineer to join  a leading investment management firm. In this role, you will design, develop, and deploy machine learning models and AI-driven solutions to enhance trading strategies, portfolio optimization, risk management, and financial forecasting. You will work closely with quant researchers, data scientists, and software engineers to leverage AI for making data-driven investment decisions.

Key Responsibilities

• Develop and optimize machine learning models for financial market predictions, portfolio management, and risk assessment.
• Build AI-powered analytics tools and data pipelines to process large-scale financial datasets.
• Research and implement cutting-edge deep learning, NLP, and reinforcement learning techniques for investment strategies.
• Work closely with quantitative researchers and traders to integrate AI models into trading and risk systems.
• Improve model performance through feature engineering, hyperparameter tuning, and model validation.
• Ensure AI models are explainable, robust, and aligned with regulatory requirements.
• Optimize execution speed and efficiency, leveraging distributed computing and cloud infrastructure where necessary.

Required Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Mathematics, or a related field.
• Strong programming skills in Python and experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience working with financial data and applying AI/ML models in an investment or trading context.
• Familiarity with time-series forecasting, NLP, reinforcement learning, and generative AI techniques.
• Proficiency in data engineering, big data processing (Spark, Dask, Kafka), and cloud computing (AWS, GCP, Azure).
• Strong understanding of statistical modeling, probability, and optimization techniques.
• Ability to collaborate with quant researchers, portfolio managers, and technology teams.

Preferred Qualifications

• Experience working in a hedge fund, asset management, or proprietary trading firm.
• Knowledge of market microstructure, options pricing, and quantitative trading strategies.
• Familiarity with C++ or Rust for low-latency AI model execution.
• Prior experience in automated trading systems, alternative data, or AI-driven portfolio optimization.

This is an exciting opportunity to work at the intersection of AI and finance, solving real-world problems with cutting-edge technology. If you thrive in a fast-paced, intellectually challenging environment, we’d love to hear from you.

Looking for Finance Data Scientist for a discreet fund in the UAE, sitting at the intersection of AI and Investment.

This position is dedicated to refining and enhancing outputs from large language models (LLMs) for financial applications, ensuring that the content is accurate, coherent, and logically consistent.

Key Responsibilities

• Oversee and enhance the quality control processes for financial content generated by LLMs
• Create and implement data pipelines for the processing and analysis of financial text data
• Work closely with the algorithm team to improve model performance and accuracy
• Provide domain expertise to enhance the representation of financial knowledge in LLM outputs
• Develop and apply quality metrics to assess model outputs
• Engage in development cycles and knowledge-sharing sessions with technical teams

Required Qualifications

• Bachelor’s degree in Finance, Economics, Computer Science, or a related discipline. Masters is a plus.
• 2+ years of professional experience in finance (funds, banks, fintech etc) or data science firms for finance.
• Strong grasp of macroeconomics, financial markets, and investment principles
• Experience with Python programming, particularly with pandas and data processing libraries
• Experience with machine learning libraries and frameworks
• Understanding of financial data sources and APIs
• Capability to design and implement data pipelines and workflows effectively
• Exceptional analytical and problem-solving abilities
• Strong communication skills with the ability to convey complex financial concepts clearly

Preferred Qualifications

• Familiarity with LLM fine-tuning and optimisation techniques
• Knowledge of NLP methods

ML Researcher (HFT) – Boutique Prop Trading firm – Amsterdam/London – Up to £750k+

A Machine Learning Researcher role for a Prop Trading Firm, being instrumental in pioneering research and advancing the development of high-frequency trading (HFT) strategies through the application of ML, DL, and RL techniques.

Your specialised knowledge will drive the automation of the quest for optimal trading strategies, ensuring our sustained success in the dynamic realm of finance.

This opportunity is based in Amsterdam, but the business is happy to relocate and sponsor suitable candidates from London/abroad.

The business has developed state-of-the-art infrastructure built by ACM ICPC World Champions and experienced Engineers from the top Prop firms globally. They trade every asset class and some crypto but are looking to venture into emerging markets.

Culture:

The setup of the business is small collaborative teams, where you aren’t restricted to working on specific areas, you have full reign covering everything from idea generation to implementation and monitoring of live strategies. They heavily leverage ML within their infrastructure which has proven to give them a significant edge in the market.

They have plenty of support in place with centralised functions providing all the tools and infrastructure you need to focus on the more important and interesting aspects of research.

Requirements:

• Possess a minimum of 3 years of experience within a high-performing ML team, refining your skills and expertise;
• Demonstrate a robust understanding of mathematical statistics and probability theory to make informed, data-driven decisions;
• Exhibit proficiency in Python programming for the effective implementation of ML algorithms;
• Showcase exceptional problem-solving abilities and thrive in a fast-paced environment;

Benefits:

• Can offer large guaranteed comp (and maybe profit share) for the right candidate.
• Offer sponsorship, relocation packages, secure property, provide moving services and help with the tax discount setup.
• High impact roles with very strong engineering and infrastructure teams.
• Lots of company trips and internal competitions with great prizes (holidays etc).

For more information or a discrete discussion about opportunities similar to the above, please feel free to get in touch at [email protected]

**Significant compensation on offer for any referrals for this position**