Data Scientist

Key Skills

Business Intelligence, Data Analytics, Data science techniques, Effective communication skills, Microsoft-Excel, Planning and organization, PowerBI, Python Programming, R Programming, SQL, Tableau

Job Description

We are seeking a Lead Program Development & Evaluation Analyst (Data Scientist) (GC 14) who will be responsible, under the general direction of the group leader of the Training Analytics Group (TAG), part of the Training & Development organization, for conducting program evaluation and training analytics projects across the scope of objectives and deliverables of the organization, either independently or in collaboration with others.

The incumbent is expected to proactively identify problems and issues that arise in his/her assigned areas and recommend solutions for these issues. The expected supervision and guidance for the position are minimal.

Key Responsibilities

• Gather training-related data from the different organizations in Training & Developing.
• Validate and verify the obtained data and suggest, if needed, methods to improve data quality.
• Seek opportunities to automate data-collection processes.
• Ensure the security, integrity and availability of a data repository/database to support the objectives and deliverables of the organization.
• Design and maintain an integrated system of dashboards to track performance training-related metrics.
• Provide analytical findings & recommendations related to training analytics and program evaluation.
• Conduct pilot studies and experiment design to evaluate new training interventions.
• Conduct predictive analysis to forecast the outcomes of training programs.
• Performs other related tasks and analytical duties with minimal supervision, as assigned.

Minimum Requirements

As a successful candidate, you must hold a bachelor's degree in Statistics, Data Science, Business Analytics, or a related discipline with at least 12 years of relevant experience. Or you must have a master degree in Statistics, Data Science, Business Analytics with a bachelor degree in Engineering, computer science, physical sciences or a related discipline with at least 12 years of relevant experience.

You must have demonstrable work experience in Statistics, Data Science, and demonstrated capability in creating dashboard systems and the use of business intelligence tools. Additionally, a solid knowledge and understanding of relational and non-relational databases, SQL, Power BI, Tableau, Excel, R, or Python is highly desirable.

It is preferred to have an advanced degree (e.g., M.Sc. or Ph.D.) in areas related to Statistics, Data Science, Data Analytics, and Research Methods.

You must have an excellent ability to communicate in English with peers as well as members of management and be able to produce clear and concise oral and written reports in English.

Desired Competencies

The following are some of the highly desired competencies for a successful candidate:

• Knowledge in data analytics/ business intelligence tools.
• Experience in designing and maintaining relational and non-relational databases.
• Experience in designing and maintaining dashboards for performance monitoring.
• Experience in quantitative and qualitative research methods applied to learning / training.
• Experience in evaluation of industrial and professional training programs.
• Solid practical knowledge in Microsoft Office; including: Power BI, Word, Excel, PowerPoint and Access.
• Solid practical knowledge in statistical programming and data mining tools; including: R, Python, and Alteryx.
• Strong presentation and communication skills.
• Fluent in English writing and speaking.

Working environment

Our high-performing employees are drawn by the challenging and rewarding professional, technical and industrial opportunities we offer, and are remunerated accordingly.

At Aramco, our people work on truly world-scale projects, supported by investment in capital and technology that is second to none. And because, as a global energy company, we are faced with addressing some of the world’s biggest technical, logistical and environmental challenges, we invest heavily in talent development.