Senior Data Scientist: Downhole Analytics for Oil & Gas

Weatherford; Houston (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Weatherford is seeking a Data Scientist to join its Sciences team in Houston to apply advanced analytics, machine learning, and scientific modeling to downhole tools, signal processing, and formation evaluation.

The role requires a strong foundation in applied mathematics and data science, with experience in large datasets, and collaboration across engineering teams to translate business needs into analytical solutions. Travel and diverse data sources are expected.

Qualifications

• Master's degree in a quantitative field and relevant domains.
• 5+ years of experience in Oil & Gas industry and data science.
• Strong analytical and problem-solving skills with ability to communicate results.

Responsibilities

• Design and develop data pipelines for cleaning, validation, and analysis of large datasets.
• Analyze structured and unstructured data to identify trends, patterns, and anomalies.
• Develop and deploy machine learning models and statistical algorithms.
• Automate data workflows and analysis using modern programming tools.
• Build predictive and physics-informed models to support tool development and characterization.
• Collaborate with engineers, physicists, and product teams to translate business needs into analytical solutions.
• Communicate insights and results effectively to technical and non-technical stakeholders.

Skills

Analytical skills

Problem solving

Communication & presentation

Data management & interpretation

Machine learning techniques

Statistical & data mining techniques

Tool physics & characterization

Education

Master's degree in applied mathematics, Data Science or Physics

Tools

C

C++

Java

JavaScript

Python

R

SQL

Job description

Weatherford is seeking a Data Scientist to join its Sciences team in Houston to apply advanced analytics, machine learning, and scientific modeling to downhole tools, signal processing, and formation evaluation.

The role requires a strong foundation in applied mathematics and data science, with experience in large datasets, and collaboration across engineering teams to translate business needs into analytical solutions. Travel and diverse data sources are expected.