1

Overnight Geology Data Science Jobs (NOW HIRING)

This Data Science Geologist will bridge traditional earth sciences with advanced data science and analytics to drive more informed subsurface decisions. This role focuses on automating geological ...

The Data Science Manager is responsible for leading a team of data scientists (individual ... Typically requires overnight travel 5% to 20% of the time. Physical Requirements: * Most of the ...

... in Geology, Earth Sciences, or related field. * Previous experience in underground geology, ore control, or production geology preferred. * Strong mapping, sampling, and geological data ...

Ensure robust QA/QC for all geological data and interpretations, and drive implementation of ... Master's degree in Geology, Geological Engineering, or a related field; or Bachelor of Science ...

Ensure robust QA/QC for all geological data and interpretations, and drive implementation of ... Master's degree in Geology, Geological Engineering, or a related field; or Bachelor of Science ...

Ensure robust QA/QC for all geological data and interpretations, and drive implementation of ... Master's degree in Geology, Geological Engineering, or a related field; or Bachelor of Science ...

Geologist

Costa Mesa, CA · On-site

$70K - $85K/yr

... engineering geology data and generate accurate and concise documentation, ensuring that ... scientific and non-scientific audience. * Proficient self-leadership with attention to detail ...

next page

Showing results 1-20

Overnight Geology Data Science information

See salary details

$37.5K

$122.7K

$196.5K

How much do overnight geology data science jobs pay per year?

As of May 28, 2026, the average yearly pay for overnight geology data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Overnight Geology Data Science vs Geology Data Analyst?

AspectOvernight Geology Data ScienceGeology Data Analyst
Required CredentialsDegree in Geology, Data Science, or related fields; proficiency in data analysis toolsDegree in Geology, Earth Sciences, or related fields; skills in data analysis and reporting
Work EnvironmentNight shifts, field sites, or office-based; focus on data processing and analysisDay shifts, office or field; focus on data interpretation and reporting
Industry UsageMining, oil & gas, environmental consultingResearch institutions, environmental agencies, mining companies

Overnight Geology Data Science involves working primarily during night shifts, focusing on advanced data analysis, modeling, and processing related to geological data. In contrast, Geology Data Analysts typically work during regular hours, emphasizing data interpretation, reporting, and supporting decision-making in geological projects. Both roles require strong analytical skills and a background in geology or related fields, but their work hours and specific focus areas differ.

What cities are hiring for Overnight Geology Data Science jobs? Cities with the most Overnight Geology Data Science job openings:
What are the most commonly searched types of Geology Data Science jobs? The most popular types of Geology Data Science jobs are:
What states have the most Overnight Geology Data Science jobs? States with the most job openings for Overnight Geology Data Science jobs include:
Data Science Geologist

Data Science Geologist

Diamondback Energy

Midland, TX • On-site

Full-time

Posted 3 hours ago


Job description

CURRENT EMPLOYEES - Please apply using "Jobs Hub" in Workday. This career site is for external applicants only.
This Data Science Geologist will bridge traditional earth sciences with advanced data science and analytics to drive more informed subsurface decisions. This role focuses on automating geological workflows, integrating complex subsurface datasets, and developing predictive and geospatial models to improve reservoir characterization, resource discovery, and development outcomes. The position plays a critical role in translating advanced analytical insights into actionable guidance for both technical teams and business leadership.
Job Responsibilities:
Include but are not limited to
  • Predictive Modeling: Develop and apply machine learning and geospatial models to identify geological features and predict reservoir quality.

  • Data Integration: Clean, integrate, and analyze diverse datasets, including seismic, well log, geochemical, rock-based, and petrophysical data.

  • Spatial Analysis: Leverage GIS and subsurface mapping tools to perform complex spatial analysis and create interactive geological models and maps.

  • Automated Workflows: Design, build, and maintain data pipelines to automate routine geological analysis and reporting.

  • Stakeholder Communication: Translate complex technical analyses into clear, actionable insights for technical teams and business stakeholders.

Required Qualifications:
  • Bachelor's degree in Geoscience or a related field

  • Minimum of 5 years of data geoscience experience

  • Proficiency in Python (Pandas, Scikit-learn, PyTorch) or R for statistical analysis

  • Expertise in SQL and industry-standard geological databases

  • Experience with GIS tools such as ArcGIS or QGIS, and/or 3D subsurface modeling software (e.g., Petrel)

  • Strong understanding of machine learning techniques (clustering, regression, anomaly detection) applied to subsurface data

  • Ability to visualize and communicate spatial data using tools such as Power BI, Tableau, or Python libraries (Matplotlib, Seaborn)

Preferred Qualifications:
  • Background in Petroleum Engineering

Diamondback is an Equal Employment Opportunity Employer. Diamondback provides equal employment opportunities to all qualified applicants without regard to race, sex, sexual orientation, gender identity, national origin, color, age, religion, veteran or disability status, genetic information, pregnancy, or any other status protected by law. Diamondback participates in E-Verify. Learn more about E-Verify.