About the job:
AIQ is an Abu Dhabi based joint venture company between Presight and ADNOC, which focuses on developing artificial intelligence technologies. AIQ develops and commercializes AI products and applications for the energy world. It aims to provide end-to-end solutions by using its data, cloud, and talents to develop AI solutions that seek to reduce costs and generate revenue for its clients. AIQ embodies an innovative and entrepreneurial spirit that embraces challenges to push boundaries and seeks to welcome professionals to its team that share the desire to make meaningful and impactful contributions to its mission. Always on the cutting edge of technology, AIQ provides its talent all the opportunities to thrive and excel.
About the role:
We are seeking a Senior Data Scientist to join our team operating in the Oil and Gas sector, specifically in upstream production modeling and optimization. You will work closely with cross-functional teams to analyze data, implement, deploy and maintain solutions, and deliver actionable recommendations to improve production management and maximize operational performance.
Responsibilities:
- Extract business value and complex relationships from petroleum data analysis and communicate it to other 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 real-time production environment.
- Maintain and enhance existing solutions to meet evolving business needs.
- Conduct daily project work related to ML solutions support and improvement.
- Visualize and communicate results analysis effectively.
- Present ideas, plans, and findings orally and in 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, e.g., oil and gas, chemical, refinery, or similar.
- 2 end-to-end AI solutions, implemented from idea to production, ideally with real-time streaming data.
- Strong understanding of machine learning algorithms, their strength, and weaknesses, and ability to choose an optimal one for a given business setting.
- Experience with developing robust, test-driven machine learning pipelines written in Python.
- Experience in monitoring and supporting machine learning pipelines in a production environment.
- Ability to plan development work within Agile settings, estimate task timelines and communicate the work progress.
- Experience in predictive maintenance or modeling of petroleum systems such as well multiphase flow models or ESP performance models is a big plus.
- Experience constrained optimization methods is a plus.
Key Skills:
- Proficiency in Python programming and data analysis libraries (e.g., Pandas, NumPy).
- Strong background in machine learning, statistics, linear algebra, and predictive modeling.
- Deep understanding of machine learning algorithms (e.g., PCA, LASSO, Gradient Boosting, Random Forest, Neural Networks).
- Strong proficiency in cleaning complex and sparse datasets and conducting feature engineering on the cleaned data.
- Experience with common development tools (e.g., PyCharm, Jupyter, Docker, Git).
- Theoretical and practical knowledge of constrained optimization, ideally with applications to Model Predictive Control (MPC).
- Excellent communication skills, both verbal and written.
Educational Requirements:
- BSc or MSc degree in a relevant field (e.g., Computer Science, Statistics).
- PhD degree is a plus.
