Data Scientist

Key Skills

Amazon RedShift, Amazon Simple Storage Service (S3), Apache Hadoop, Apache Hive, C Programming, C++, Coremetrics, D3.js, ggplot, Google Analytics, google-adwords, Gurobi, Java Programming, JavaScript, Large scale data processing, MapReduce, Maps Technology, MySQL, Python Programming, R Programming, Site Reliability Engineering (SRE), SPARK Programming, SQL

Job Description

Aramco occupies a unique position in the global energy industry. We are the world's largest producer of hydrocarbons (oil and gas), with the lowest upstream carbon intensity of any major producer.

With our significant investment in technology and infrastructure, we strive to maximize the value of the energy we produce for the world along with a commitment to enhance Aramco’s value to society.

Headquartered in the Kingdom of Saudi Arabia, and with offices around the world, we combine market discipline with a generations’ spanning view of the future, born of our nine decades experience as responsible stewards of the Kingdom’s vast hydrocarbon resources. This responsibility has driven us to deliver significant societal and economic benefits to not just the Kingdom, but also to a vast number of communities, economies, and countries that rely on the vital and reliable energy that we supply.

We are one of the most profitable companies in the world, as well as amongst the top five global companies by market capitalization.

Overview

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 use models to test the effectiveness of different courses of action. She/he 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. She/he 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.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 use models to test the effectiveness of different courses of action. She/he 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. She/he 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.

Key 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.

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 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, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with 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: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.