Artificial Intelligence

Overview

We are seeking an Artificial Intelligence Specialist to join Global Manufacturing Excellence (GME) Digitalization and Technology Division(D&TD). GME is the recognized Center of Excellence for driving value across Saudi Aramco’s Downstream Global manufacturing portfolio.

D&TD are responsible for providing AI-powered solutions to various functions within the GME Admin Area.

Your primary role will be to work closely with business functions, stakeholders, functional teams to give consultation on AI use case, identify potential value, formulate models and conceptualize them. Also, you will introduce, design, develop and sustain solutions leveraging the latest Artificial Intelligence (AI) and technological advancements to create and bring in business values across the business chain. This role will play a pivotal aspect in helping our organization to make data-driven decisions and to solve complex problems.

Key Responsibilities

As the successful candidate you will be required to perform the following:

• Collaborate with cross-functional teams, including engineers and domain experts, to drive data-driven improvements through AI solutions that are either built in house or precured.
• Communicate findings and insights regarding the AI solution or data being gathered to stakeholders.
• Gather and pre-process data from various industrial sources, such as sensors, Distributed Control Systems (DCS) systems, and manufacturing equipment’s while ensuring their quality and integrity.
• Analyze and clean data to identify opportunities for process optimization, energy efficiency improvements, cost reduction, or cost optimization.
• Apply statistical analysis methods to test hypotheses and validate results based on the project or use-case.
• Build and train machine learning models to solve specific problems and optimize models for performance and accuracy such as anomaly detection algorithms or predictive models.
• Bring in innovative ideas to apply image, video and audio analytics or methodologies to reduce manual efforts like visual inspection/field monitoring of industrial plants.
• Work with front-end and back-end teams on dashboards to integrate the models make them user friendly for the stakeholders.
• Maintain documentation for data analysis processes, models, and findings.
• Ensure that data practices adhere to industry regulations and data privacy standards.
• Monitor and evaluate model performance and make necessary adjustments to maintain accuracy and reliability.

Minimum Requirements

As a successful candidate you will hold a:

• Bachelors / Master’s degree in Engineering, Computer Science, Data science and analytics, Machine learning, or AI, or in a related field.
• Able to program in different languages such as python and R and has experience with statics and data cleaning libraries and methodologies, in addition to visualization such as Power BI or Tableau.
• Familiarity with popular libraries such as NumPy, Pandas, etc.
• Statistical knowledge such as descriptive statistics, analysis of variance, regression analysis, hypothesis testing and confidence intervals.
• Understand Data cleaning methodology and how to fill in missing data using certain methodologies.
• Preferably sufficient and has technical terminologies in processing and refineries if possible and applicable. 
• 5 years hands on experience, with a preference of 10 years of experience in building data analytics-based products or machine learning models.
• Proficiency in developing, evaluation and selecting the best AI solution or model and has a holistic knowledge about front-end and back-end integration to the model.
• Experience in applying optimization such as gradient descent, etc.
• Excellent communication skills with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
• Exceptional analytical and problem-solving skills, with the ability to derive insights and opportunities from data are required.
• Basic project management skills to plan, execute, and deliver data science projects on time and within scope is preferred.