Company: Baker Hughes
Skills: IT - Analysis & Management, Research & Development
Experience: 6 + Years
Education: Masters Degree
Employment Type: Full Time Salaried Employee
Location: Claremore, Oklahoma, United States

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.

Role Summary:


The position is for a Data Scientist who will work as part of the Artificial Lift Systems Research and Technology Development team. Said team is tasked with researching, conceptualizing, designing and qualifying next generation artificial lift systems. The candidate will work in an innovative, challenging and rewarding environment with a team of highly qualified professionals focused on pushing the limits of artificial lift technology through customer focus, creative thinking, research, design, analysis, prototyping, engineering test and field testing. The candidate will interact with customers, subject matter experts, data scientists, engineers and software developers to create and validate new analytic solutions to be integrated into internal business solutions or external commercial product offerings.

Essential Responsibilities:
  • Work with external/internal customers, engineers and data scientists to define the problem statement, requirements and scope for data science projects related to the areas of prognostics, diagnostics and system control
  • Research, develop, validate and apply data science, machine learning or other analytical methods to support internal business needs and delivery of analytic features for Artificial Lift Systems commercial product offerings
  • Work alongside software developers and software engineers to integrate data science and machine learning algorithms into commercially viable technology that can be incorporated into products and services
  • Lead data analytics activities related to data quality assessments, data requirement definition, data cleansing, data structuring and analytical model development
  • Perform exploratory and targeted data analyses using descriptive statistics and other methods
  • Develop and apply Machine Learning, Deep Learning and data science modeling techniques for time-series analytics including anomaly detection, data mining, pattern recognition, smart alarming and remaining useful life prediction
  • Apply classification techniques via supervised/unsupervised learning, automated feature generation and feature engineering
  • Deploy the solutions into oilfield platforms, evaluate model performance, and establish automated workflow to enable model re-training and self-learning capabilities
  • Generate reports, annotated code, and other project artifacts to document, archive, and communicate the work and outcomes
  • Support analytics framework development through collaboration with universities, analytics researchers, data scientists and other engineering disciplines including mechanical, electrical, petroleum and chemical
  • Provide inputs on best practices, industry trends, and future potential for industrial analytics
  • Support the development of project plans by developing: task lists, engineering estimates, resource requirements, project schedules, technical risk assessments and mitigation plans
  • Develop and document technical requirements in accordance with team standards
  • Capability to effectively collaborate with other functions such as Supply Chain, Field Operations, Product Line Managers and Customer Relation teams to: ensure project tasks are completed within allocated schedule and budget, develop understanding of business operations, and disseminate technical knowledge
  • Interface with internal and external customers in professional manner
  • Perform special projects as required

  • Degree in Engineering (Mechanical or Electrical): Bachelor's Degree with 6+ years' experience, Master's Degree with 4+ years' experience. Work experience shall be in area of data science, machine learning, and/or deep learning.
  • Legal authorization to work in the US. We will not sponsor individuals for employment visas for this position
  • Excellent written and verbal communication skills
  • Ability to build strong peer relationships
  • Must be action oriented and driven to achieve results while receiving moderate to minimal supervision
  • Demonstrated ability to complete project work on time and within budget
  • Must be willing to travel
  • Must be willing to office in Claremore, OK.

Desired Characteristics:
  • Experience integrating engineering analytics or advanced data-driven analytics into software solutions
  • Demonstrated proficiency in coding in languages including but not limited to Python, Matlab, and C
  • Demonstrated skills in applying supervised/unsupervised machine learning/deep learning techniques in algorithm development (e.g. regression, classification, clustering, and neural networks etc.)
  • Demonstrated skills in the use of one or more machine learning/deep learning frameworks (e.g. TensorFlow, Keras, Caffe2, Theano, Torch, CTPN etc.) in time-series data
  • Good CPU/GPU parallel computing knowledge and algorithm performance tuning knowledge
  • Strong background in deep learning and modeling techniques (RNN, CNN, DNN, ANN, DBN etc.)
  • Experience working with big data technologies to ingest, process and store structured and un-structured data in rest and in motion using Hadoop, Spark, Microsoft Azure, Google Cloud Platform (GCP) and/or Amazon Web Services (AWS) technologies
  • Experience working in an innovation and research environment
  • Effective teaming and problem-solving abilities with strong interpersonal and leadership skills
  • Proven ability to think customer-first and effectively prioritize and pivot as required
  • Experience in oil and gas industry and familiarity with unconventional oil & gas asset technologies


Claremore, Oklahoma