Digital Data Scientist-Time Series Forecasting


Position description

Saudi Aramco is seeking an experienced Digital Data Scientist specializing in time series forecasting to join the Digital Transformation AI & Analytics organization (DT AI&A).

The Digital Transformation AI & Analytics organization (DT AI&I) is responsible for providing AI-powered solutions to various business functions within Aramco. The solutions leverage the latest technological advancements of Artificial Intelligence (AI) and analytics to create business values across the value chain. The DT AI&A organization will be a center of excellence in Saudi Aramco for Artificial Intelligence technologies and data science.

The digital data scientist primary role is to work closely with business functions, stakeholders, functional teams to give consultations on AI use case, identify potential value from data, formulate AI and data science ideas and conceptualize them. In addition, to building, evaluating and productionalizing models as appropriate.


Minimum requirements

The successful candidate should have:

  • A Master’s degree in in data science, computer science, computer vision, applied mathematics or a related field from a recognized and approved program. A PhD degree is preferred.
  • At least 5 years of experience in building time series forecasting models.
  • Very strong expertise in data collection, cleaning, preprocessing, and wrangling is a requirement.
  • Fluent in either R or Python, preferably both, and familiarity with golang is a plus.
  • Proficiency in visualization tools and packages; and in communicating data science topics to non-technical audience is a requirement.
  • Experience in time series forecasting models and in using technologies like LSTMs, Prophet, and time series analysis is a requirement.
  • Proficiency in using sklearn pandas, numpy, plotly, seaborn, and relevant R libraries if R is their preferred language is necessary.


Duties & responsibilities

You will be required to perform the following:

  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
  • Mine and analyze data from company data sources to drive optimization and improvement of product development, and business strategies.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Develop custom data models and algorithms as needed and appropriate to address problems at hand
  • Use predictive modeling and time series forecasting to increase and optimize production facilities, revenue generation, and other targeted outcomes.
  • Develop A/B testing mechanisms and test model quality and value, and validate hypothesis accordingly.
  • Coordinate with different functional teams to implement models and monitor outcomes.
  • Develop necessary documentation as per established standards.


How to apply

If you believe you meet the requirements for this role, please contact us with your CV and state "AAS - [Job Title]" in the subject line. 

Apply now