Quantitative AI

2 weeks ago

Dubai, Dubai, United Arab Emirates Durlston Partners Full time

The Role

As a
Quantitative AI / Machine Learning Data Science Researcher
, you will play a pivotal role in developing
data-driven investment models
and
AI-enhanced research pipelines
that inform our trading and portfolio management strategies. You will work closely with portfolio managers, quantitative analysts, and engineers to apply
state-of-the-art machine learning methods
,
alternative data
, and
large-scale computation
to extract predictive insights and optimise investment decisions.

Key Responsibilities

  • Research, design, and implement
    machine learning and statistical models
    for forecasting, risk modelling, and alpha generation.
  • Explore and process
    large, complex datasets
    , including alternative and unstructured data sources.
  • Develop scalable tools and pipelines for
    data analysis, feature engineering, and model validation
    .
  • Collaborate with portfolio managers and engineers to integrate research outputs into
    live trading systems
    .
  • Stay abreast of advances in AI, deep learning, and quantitative finance, and drive innovation across research teams.

About You

  • Advanced degree (PhD or MSc) in a
    quantitative discipline
    such as Mathematics, Computer Science, Statistics, Physics, or Engineering.
  • Demonstrable experience in
    machine learning, AI research, or quantitative modelling
    , ideally within financial markets or a research environment.
  • Strong programming skills in
    Python, C++ or Julia
    , and familiarity with ML frameworks such as
    PyTorch or TensorFlow
    .
  • Solid understanding of
    statistical inference, optimisation, and time-series modelling
    .
  • Experience with
    big data technologies
    (e.g. Spark, distributed computing) would be advantageous.
  • Highly analytical, intellectually curious, and able to communicate complex ideas clearly and effectively.

What We Offer

  • The opportunity to work alongside
    world-class researchers and technologists
    on challenging, high-impact projects.
  • Competitive salary and
    performance-related bonus
    .
  • Access to
    extensive proprietary and alternative datasets
    .
  • Support for
    research publication, conference participation
    , and professional development.
  • A collaborative culture that values
    innovation, scientific rigour, and continuous learning
    .

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