Data Scientist

Saudi Aramco (ASC)
Saudi Arabia
  • 1
1 + Years Experience

Company: Saudi Aramco (ASC)
Skills: IT - Analysis & Management
Experience: 1 + Years
Education: Masters Degree
Employment Type: Full Time Salaried Employee
Location: Saudi Arabia

In order to apply for this position, applicants MUST meet the following criteria. If your resume does not match these criteria, you will not be able to apply for this position.

Req Number: 17623BR

Position Description:
We are searching for a Data Scientist who will support our facility management organization with insights gained from analyzing company data and to support data-driven initiatives. The ideal candidate is adept at using large data sets to find opportunities for process optimization and the use of models to test the effectiveness of different courses of action. The candidate must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. The candidate must have a proven ability to drive business results with data-based insights, and must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
The ideal candidate will also have experience and expertise in sourcing and establishing sources of reliable/accurate data, and establishing controls to ensure data integrity.

Minimum Requirements:
Candidate must meet the following minimum requirements:

Strong problem solving skills with an emphasis on product development.

Experience using statistical computer languages (i.e., R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.

Experience working with and creating data architectures.

Knowledge of a variety of machine learning techniques (i.e., clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

Knowledge of advanced statistical techniques and concepts (i.e., regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

Excellent written and verbal communication skills for coordinating across teams. Able to explain the "so what" of data findings in a clear manner.

Driven to learn and master new technologies and techniques.

We're looking for someone with 5-7 years of experience manipulating data sets and building statistical models, with a Master's or Ph.D. degree in Statistics, Mathematics, Computer Science, or another quantitative field, and is familiar with the appropriate software/tools, which may include:

Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.

Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.

Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.

Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.

Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.

Experience analyzing data from 3rd party providers:

Duties & Responsibilities:
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

Assess the effectiveness and accuracy of new data sources and data gathering techniques. Drive establishment of high-integrity data sources and processes.

Develop custom data models and algorithms to apply to data sets.

Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.

Develop testing framework and test model quality.

Coordinate with different functional teams to implement models and monitor outcomes.

Develop processes and tools to monitor and analyze model performance and data accuracy.

Support digital transformation efforts and link data sources to useful dashboards, monitoring systems, and KPI tracking.

About us: