Senior Data Scientist

ManpowerGroup Middle East; Dubai; On-site; AED 200,000 - 300,000; Full time

Job summary

A leading company in the energy sector seeks a Senior Data Scientist to enhance the Field Development Integration Catalog through advanced analytics and AI/ML models. The ideal candidate will have a proven track record in data science, particularly in oil and gas, with a strong foundation in reservoir engineering. This role involves collaboration with multidisciplinary teams to deliver innovative solutions and support efficient hydrocarbon maturation processes.

Qualifications

• 5-7 years of relevant experience in data science, preferable in oil and gas.
• Strong understanding of reservoir engineering and dynamic simulation.
• Formal data science certifications or qualifications preferred.

Responsibilities

• Design, train, and validate AI/ML models for reservoir simulation outcomes.
• Integrate AI models into the FDIC dashboard.
• Extract, clean, and harmonize data from thematic studies.

Skills

Descriptive statistical modeling

Machine learning

Deep learning

Reinforcement learning

Optimization

Pattern recognition

Data visualization

Strong analytical mindset

Problem-solving

Education

Bachelor's or master's degree in data science

Degree in petroleum engineering, computer science, or related discipline

Tools

Python

TypeScript

Scikit-learn

TensorFlow

PyTorch

Plotly

Streamlit

Django

Flask

Angular

Git

Azure DevOps

Job description

Purpose of the job

The senior data scientist will play a key role in advancing and operationalizing the Field Development Integration Catalog (FDIC) through cutting-edge analytics and artificial intelligence. This role focuses on developing, deploying, and maintaining AI/ML models and tools that accelerate and enhance Field Development Planning (FDP). By leveraging reservoir analogues and historical data from thematic studies, the data scientist will directly contribute to the company's strategy for efficient hydrocarbon maturation amid the evolving energy transition.

Required skills, knowledge, experience & qualifications

• Bachelor's or master's degree in data science, petroleum engineering, computer science, or a related discipline.
• 5-7 years of relevant experience in data science, preferably in the oil and gas sector.
• Proficiency in advanced analytical techniques, including:
  • Descriptive statistical modeling
  • Machine learning and deep learning
  • Reinforcement learning
  • Optimization
  • Pattern recognition, clustering, and segmentation
  • Data visualization
• Strong understanding of reservoir engineering and dynamic simulation fundamentals.
• Proficiency in programming languages and libraries such as:
  • Python, TypeScript
  • Scikit-learn, TensorFlow, PyTorch
  • Python visualization tools (Plotly, Streamlit)
  • Web frameworks (Django, Flask, Angular)
• Experience with version control tools like Git and Azure DevOps.
• Cloud computing experience is an asset.
• Familiarity with the company's thematic studies and the field development lifecycle is highly advantageous.
• Preferred: formal data science certifications or qualifications.

Key competencies

• Strong analytical and problem-solving mindset.
• Ability to clearly communicate technical information across multidisciplinary teams.
• Passion for digital transformation and innovation in the energy industry.
• Self-motivated and results-oriented with a focus on quality and value delivery.
• Collaborative approach and proactive engagement with business and technical stakeholders.

Principal accountabilities

• Design, train, and validate AI/ML models to replicate dynamic reservoir simulation outcomes.
• Integrate AI models into the FDIC dashboard to support analogue-driven FDP.
• Expand and manage a robust library of predictive models based on reservoir analogues.
• Extract, clean, and harmonize data from thematic studies and simulation models.
• Translate reservoir engineering insights into data science features in collaboration with subject matter experts.
• Ensure seamless integration of AI tools within the FDIC website and HMC platform through close collaboration with digital teams.
• Enhance the dashboard's UI/UX to meet the needs of a diverse user base.
• Apply data science methods to identify and recommend development scenarios based on relevant analogues.
• Support agile and streamlined FDP generation through structured FDIC workflows.
• Define governance frameworks and update mechanisms for sustainable FDIC operations.
• Lead initiatives for model performance tracking, feedback incorporation, and version control.