Data Scientist – Machine Learning / Deep Learning

Job Reference: 251658

Upstream


Start Date: 01/09/2026
Applications close on: 28/08/2026
Contract Type: Contract
Country: United Arab Emirates
Discipline: IT and Software
Job Contact: [email protected]

Data Scientist – Machine Learning / Deep Learning

We are currently looking for an experienced Data Scientist to join an exciting engineering-focused project.

The ideal candidate will have 4–5 years of professional Data Science / Machine Learning experience and strong hands-on knowledge of both Classical Machine Learning and Deep Learning.

Key Requirements:

  • 4–5 years’ professional Data Science / Machine Learning experience
  • Strong Python programming skills
  • Hands-on experience with Classical Machine Learning and Deep Learning
  • Strong understanding of Neural Networks
  • Experience with data preprocessing and feature engineering
  • Model evaluation and hyperparameter tuning experience
  • Good working knowledge of SQL
  • Experience working with small, noisy or complex datasets

Desirable Experience:

  • Time-series or sequential data
  • Physics-Informed ML or hybrid Physics + ML modelling
  • Engineering, scientific or industrial datasets
  • Cloud platforms and MLOps/deployment workflows

The Role:

You will work across the full ML/DL lifecycle, including data preparation, predictive modelling, model validation, deployment and continuous improvement.

This is an excellent opportunity to work on real-world engineering data and develop scalable predictive solutions using Machine Learning, Deep Learning and Neural Networks.

Benefit of Working with Visuna?

  • A dedicated member of the team responsible for your placements and welfare
  • Some of the best day rates in the industry
  • FREE worldwide insurance and Medevac cover whist on a Placement
  • 24/7 access to our specialist support team
  • Assistance and advice on a range of business topics
  • FREE access to our Competency Scheme
  • Increased exposure to potential clients and more placement opportunities
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