Data Science Technical Fellow

4 weeks ago

Houston, United States Patterson-UTI Full time
Job Description

Patterson-UTI Drilling

The New Standard for Drilling Performance

Drill safer, smarter and faster with Patterson-UTI Drilling's comprehensive fleet of pad-capable rigs featuring advanced walking systems to enhance your operations so you can reach your apex.

Patterson-UTI's Data Science team is a growing group of energetic, passionate individuals working to improve and inform the Company through data. We work exclusively with the Drilling Automation team to help design, evaluate, and improve novel drilling automation technology.

Some example projects that we are applying analytics and data science to include:
  • Modeling greenhouse gas emissions from the rig fleet to reduce environmental impact and improve reporting
  • Designing drilling advisory systems to improve drilling efficiency
  • Developing automated monitoring, detection, and alerting of operational events
  • Building models to predict failure of downhole and surface equipment
With the growing focus on use of data science to improve operational performance, we are creating this new position on the team. The Technical Fellow will be responsible for broadly advising the Data Science team on project scope and technical direction, as well as applying their skills to personal projects.

She / he will manage analytics projects of varying complexity, along with coaching and mentoring more junior individuals on the team. Projects include creating actionable reports, algorithms, and models that will directly impact the development of new automation technologies.

For individual work, the candidate will be involved in all aspects of the project life cycle, including interviewing stakeholders to define objectives, cleaning and analyzing data, generating visuals and reports, and presenting results. The most complicated research-oriented projects will be reserved for the candidate, with resources assigned from the larger group as needed for assistance and personnel development.

For other projects on the team, the candidate will use their experience to provide guidance on technical direction including research methodologies, algorithm and analysis recommendations, and field deployment strategies for data science products.

This role performs under general direction of the Lead Data Scientist.

Detailed Description:
  • Mentor and coach a team of data scientists working on a variety of projects
  • Provide guidance on algorithm design, research, deployment, and general operations to the data science team as a whole
  • Become the subject matter expert on projects, including visiting rigs to gain a deeper understanding of drilling rig operations
  • Understand and demonstrate the importance of applying operational know-how to technical solutions for the developing the best outcomes in the most efficient manner possible
  • Be responsible for multiple analytics projects of varying complexity and data sources, typically lasting ~1 week to ~3 months in duration using time series and relational databases
  • Independently manage and execute projects from start-to-finish, including understanding stakeholder needs; acquiring necessary data; cleaning / analyzing data and innovating beyond initial requirements; generating visuals / reports; and presenting results to stakeholders
  • Identify and research opportunities for more advanced data science solutions, alternative approaches, and new technologies
  • Be the focal point for analytics: work and communicate with multiple stakeholders, understand project requirements, and deliver analytics solutions that add business value
  • Perform coding in accordance with coding standards, version control and minimize defects through unit testing
Job Requirements
  • Prior experience applying data science techniques to oil and gas drilling data
  • Familiarity with drilling automation systems
  • Experience mentoring, and coaching a team of data scientists
  • Expert in Python to generate analyses, algorithms, and visuals
  • Able and willing to visit a drilling rig location on a semi-regular basis to gain subject matter knowledge
  • Able to clearly articulate complex data science techniques to end-users that have minimum technical background
  • Have excellent soft skills to gain rapport within the organization and seek out buy-in for our team
  • Able to work both independently and as part of a team, managing multiple tasks and projects simultaneously to meet challenging deadlines
  • Excellent verbal and written communication skills
Minimum Qualifications
  • Master's degree in Engineering, Computer Science, Physics, or related field
  • 5+ years' applying data science techniques to oil and gas automation projects
  • 3+ years' experience in Python for data analysis and visualization (such as Jupyter Notebooks, Pandas, Numpy, Matplotlib)
  • Previous experience working in cross-functional roles and communicating directly with product stakeholders
Preferred Qualifications
  • PhD in Engineering, Computer Science, Physics, or related field
  • Previous experience with drilling automation control systems
  • Previous experience coaching data scientists
  • Previous field experience working on on- or off-shore drilling rigs
  • Portfolio of patents or research publications related to oil and gas drilling


Additional Details:

This position requires the person to be able to work in a time sensitive, high visibility role and regularly travel as needed to support business units and to visit work sites. It may also require extended travel to remote locations and/or overnight stay(s) during variable hours. Variable work hours include hours worked on the weekend, on holidays, and hours to travel within and outside of the assigned region. Must work with an emphasis on planning, multitasking, and prioritization to maximize efficiency of the team. Must be able to work closely with others and manage customer interaction in a professional manner. Ability to safely navigate work sites with occasional walking, climbing, standing, stepping, working at heights, etc., during normal operating conditions (day/night, outdoor hot/cold weather) and while utilizing designated personal protective equipment (PPE).

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