Pay
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Houston, TX, United States
Live, first seen by us 22 days agoOwn analytics projects start to finish, from stakeholder needs to final presentation
Mentor and coach other data scientists and analysts
Design drilling advisory systems that improve efficiency
Build automated monitoring, detection, and alerting for operational events
Develop models that predict downhole and surface equipment failures
you'll own analytics projects from first stakeholder conversation to final presentation
Mentor and coach other data scientists and analysts
Designing drilling advisory systems that improve efficiency
Building automated monitoring, detection, and alerting for operational events
Developing models that predict downhole and surface equipment failures
Developing models that predict downhole and surface equipment failures This is an individual contributor role reporting to the Senior Manager, Data Science. We're looking for someone who is technically strong in Python and time-series analysis, comfortable explaining complex methods to non-technical audiences, and excited to work alongside the people who run the rigs. This is an applied research role with impact on real world operations. Detailed Description:Read the full posting
Bachelor’s degree in Engineering, Physics, Computer Science or related field
5 years of experience applying data science techniques specifically to industrial operational data (i.e. Oil and Gas, chemicals, manufacturing, etc.)
3 years of experience in Python for data analysis and visualization (including Jupyter Notebooks, Pandas, Numpy, Matplotlib)
3 years of experience using scikit-learn or equivalent software
3 years of experience analyzing time series data
3 years of experience using SQL for data extraction and manipulation
Master’s degree or higher in Engineering, Physics, Computer Science or related field
Minimum Qualifications - Bachelor’s degree in Engineering, Physics, Computer Science or related field - 5 years of experience applying data science techniques specifically to industrial operational data (i.e. Oil and Gas, chemicals, manufacturing, etc.)
Preferred Qualifications - Master’s degree or higher in Engineering, Physics, Computer Science or related field - Over 2 years of experience applying data science techniques to data generated from oil and gas drilling operations
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$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Day 22
Similar jobs usually come down between day 7 and day 56.
From 10,198 similar postings that came down. Coming down is not always a hire.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Developing models that predict downhole and surface equipment failures This is an individual contributor role reporting to the Senior Manager, Data Science. We're looking for someone who is technically strong in Python and time-series analysis, comfortable explaining complex methods to non-technical audiences, and excited to work alongside the people who run the rigs. This is an applied research role with impact on real world operations. Detailed Description:
- 5 years of experience applying data science techniques specifically to industrial operational data (i.e. Oil and Gas, chemicals, manufacturing, etc.) - 3 years of experience in Python for data analysis and visualization (including Jupyter Notebooks, Pandas, Numpy, Matplotlib) - 3 years of experience using scikit-learn or equivalent software
- 3 years of experience analyzing time series data - 3 years of experience using SQL for data extraction and manipulation - 1 year of experience using Git for code management
- Over 2 years of experience applying data science techniques to data generated from oil and gas drilling operations - Over 2 years of experience using PowerBI or other business intelligence tools - Over 2 years of experience developing and deploying models at the edge
- 3 years of experience in Python for data analysis and visualization (including Jupyter Notebooks, Pandas, Numpy, Matplotlib) - 3 years of experience using scikit-learn or equivalent software - 3 years of experience analyzing time series data
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New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Patterson-UTI's Data Science and Analytics team turns rig data into better drilling. We partner primarily with the Drilling Automation team to design, test, and refine new automation technology, using analytics, machine learning, and artificial intelligence to make drilling safer and more efficient.
As a Senior Data Scientist, you'll own analytics projects from first stakeholder conversation to final presentation, mentor junior teammates, occasionally spend time on rigs to test new technology or understand the operations behind the data.
Projects you may work on include:
This is an individual contributor role reporting to the Senior Manager, Data Science. We're looking for someone who is technically strong in Python and time-series analysis, comfortable explaining complex methods to non-technical audiences, and excited to work alongside the people who run the rigs. This is an applied research role with impact on real world operations.
Detailed Description:
Mentor and coach other data scientists and analysts
Execute as an individual contributor multiple analytics projects of varying complexity and data sources (~1 week to ~3 months; time series and relational databases)
Become the subject matter expert on projects, including visiting rigs to gain a deeper understanding of drilling rig operations.
Maintain standards on code quality and code management
Be the focal point for analytics: work and communicate with multiple stakeholders, understand project requirements, and deliver analytics solutions that add business value
Assist with developing and improving our suite of data analytics applications and visualizations, including developing requirements and working with developers
Independently manage and execute above 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 opportunities for more advanced data science solutions
Job Requirements
Prior experience in oil and gas data analytics
Expert in programming to generate analyses, algorithms, and visuals
Able to 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 analytics team
Able to work both independently and as part of a team, managing multiple tasks and projects simultaneously to meet challenging deadlines
Able to think strategically and translate concepts into action plans and track results
Able and willing to occasionally visit a drilling rig location to gain subject matter knowledge
Excellent verbal and written communication skills
Represent the data science team by presenting drilling intelligence, automation products, and AI/ML initiatives to customers and end users, while representing Patterson-UTI at internal and external events, including marketing and sales engagements
Capable of leading a small team of data analysts and data scientists, with the potential to grow into a Lead Data Scientist role
Minimum Qualifications
Bachelor’s degree in Engineering, Physics, Computer Science or related field
5 years of experience applying data science techniques specifically to industrial operational data (i.e. Oil and Gas, chemicals, manufacturing, etc.)
3 years of experience in Python for data analysis and visualization (including Jupyter Notebooks, Pandas, Numpy, Matplotlib)
3 years of experience using scikit-learn or equivalent software
3 years of experience analyzing time series data
3 years of experience using SQL for data extraction and manipulation
1 year of experience using Git for code management
Preferred Qualifications
Master’s degree or higher in Engineering, Physics, Computer Science or related field
Over 2 years of experience applying data science techniques to data generated from oil and gas drilling operations
Over 2 years of experience using PowerBI or other business intelligence tools
Over 2 years of experience developing and deploying models at the edge
Over 2 years of experience in any of the following:
Physical modeling of mechanical systems
Predictive maintenance or reliability modeling of equipment
Drilling automation systems
Control systems for industrial applications
Existing research publications and/or patents related to oil and gas drilling
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Houston, TX, United States
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