Nabors is a leading provider of advanced technology for the energy industry. With operations in about 20 countries, Nabors has established a global network of people, technology and equipment to deploy solutions that deliver safe, efficient and responsible hydrocarbon production. By leveraging its core competencies, particularly in drilling, engineering, automation, data science and manufacturing, Nabors aims to innovate the future of energy and enable the transition to a lower carbon world.
Nabors is committed to providing equal employment opportunities to all employees and applicants and prohibiting discrimination and harassment of any type without regard to race, religion, age, color, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This applies to all terms and conditions of employment including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. To learn more about our Fair Employment practices, please refer to the Nabors Code of Conduct.
Data Science engineer will help develop data science applications using machine learning and statistical techniques, help discover the information hidden in large and complex data sets
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
The ideal candidate is adept at developing software to acquire, process and store large volumes of data and applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with drilling products.
Candidate must have experience using a variety of data mining and statistical methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.
DUTIES AND RESPONSIBILITIES
- Leverages deep understanding of statistical techniques and tools to analyze data according to the project plan; communicates with stakeholders to provide updates and manage scope
- Use predictive modeling and machine learning algorithms to solve complex problems and drive business decisions
- Lead stakeholders on mapping requirements, researching the state-of-the-art, exploring data, running experiments, presenting the storytelling, and influencing leadership on the appropriate solution;
- Stay abreast of state-of-the-art machine learning technologies; follow code standards and best practices Develop and maintain forecasting models and tools using frameworks such as TensorFlow
- Doing ad-hoc analysis and presenting results in a clear manner
- Creating automated anomaly detection systems and constant tracking of its performance
- Use Deep Learning frameworks like PyTorch, Tensorflow and MxNet;
- Strong written and verbal communication skills, with experience engaging and influencing senior leaders
Bachelors or Masters degree in quantitative field ((Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
6-8 years of experience in analytics with at least 3 years of experience in statistical analysis
Familiar with the following software/tools:
- Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)
- Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Knowledge and demonstrable skills in Deep learning architectures and implementation usingPytorchorTensorFlow.
- Ability to implement statistical models for forecasting, time series predictions
- Experience using web services: REST API, SOAP, WCF etc.
- Experience with distributed data/computing tools: Hadoop, Hive, Spark, Oracle, MySQL, Cosmos DB, Mongo DB etc.
- Strong problem-solving skills with an emphasis on product development.
- Excellent written and verbal communication skills for coordinating across teams.
PHYSICAL REQUIREMENTS / WORKING CONDITIONS
Travel to rig for domain knowledge and new product testing.