Senior Data Scientist

About the job
AIQ, a joint venture company based in Abu Dhabi between Presight and ADNOC, is dedicated to developing artificial intelligence technologies. The company focuses on creating and commercializing AI products and applications specifically for the energy sector, with the goal of providing end-to-end solutions that reduce costs and enhance revenue for clients. AIQ champions an innovative spirit, embracing challenges and seeking professionals eager to make meaningful contributions.
We are looking for a Senior Data Scientist to join our team within the Oil and Gas sector, focusing on upstream production modeling and optimization. In this role, you will collaborate with cross-functional teams to analyze data, implement and maintain solutions, and provide actionable recommendations aimed at improving production management and maximizing operational performance.

Responsibilities:

• Extract business value and complex relationships from petroleum data analysis and share insights with team members, management, and customers.
• Identify opportunities for process optimization and equipment failure predictions using machine learning techniques.
• Develop predictive data-driven/hybrid models of petroleum production systems and equipment.
• Construct and deploy machine learning pipelines in a real-time production environment.
• Maintain and enhance existing solutions to meet evolving business needs.
• Conduct daily project work related to machine learning solution support and improvement.
• Visualize and communicate results analysis effectively.
• Present ideas, plans, and findings through oral presentations and written reports.
• Collaborate with data scientists, data engineers, and software engineers on production applications.

Qualifications:

• Professional Experience:

  • 4+ years of data science experience with a focus on data-driven modeling or predictive maintenance of engineering systems (oil and gas, chemical, refinery, or similar).
  • Experience in implementing 2 end-to-end AI solutions from conception to production, ideally involving real-time streaming data.
  • Strong understanding of machine learning algorithms and the ability to select optimal ones for specific business contexts.
  • Proven experience in developing robust, test-driven machine learning pipelines in Python.
  • Familiarity with monitoring and supporting machine learning pipelines in production environments.
  • Experience in planning development work within Agile frameworks, including estimating task timelines and communicating work progress.
  • Preferred experience in predictive maintenance or modeling of petroleum systems such as well multiphase flow models or ESP performance models.
  • Knowledge of constrained optimization methods is advantageous.

• Key Skills:

  • Proficiency in Python programming and data analysis libraries (e.g., Pandas, NumPy).
  • Strong foundation in machine learning, statistics, linear algebra, and predictive modeling.
  • Comprehensive understanding of machine learning algorithms (e.g., PCA, LASSO, Gradient Boosting, Random Forest, Neural Networks).
  • Excellent ability to clean complex and sparse datasets and conduct feature engineering.
  • Experience with development tools (e.g., PyCharm, Jupyter, Docker, Git).
  • Theoretical and practical knowledge of constrained optimization, especially related to Model Predictive Control (MPC).
  • Exceptional communication skills, both verbal and written.

• Educational Requirements:

  • BSc or MSc degree in a relevant field (e.g., Computer Science, Statistics). A PhD degree is a plus.