Junior Data Scientist, Petroleum Engineering & Well Integrity

Job Description

Job Description

Company Description

You'll learn data science on problems that matter: the work you contribute to helps operators confirm their wells are safe. As part of a small team, you'll get real responsibility early, direct access to senior experts, and a front-row view of how analytics products are built in the energy industry.

Check out for more information on our world-class team.

Job Description

Are you graduating with an engineering or quantitative degree and want to apply data science to real problems in the energy industry? IPT Global builds well integrity solutions used by operators to verify that wells are safe, and we're looking for an early-career data scientist to join our Data Science team.

You'll work alongside senior data scientists on the data behind well barrier assurance: pressure tests, cement evaluations, annulus pressure histories, and sensor data from well control equipment like BOPs. From day one you'll be part of the full analysis process, from framing the problem and cleaning messy field data through to building models and presenting what you found. This is a role built for learning, with guidance from experienced colleagues and increasing independence as your skills grow.

What you'll do

• Support analysis of well barrier assurance and verification data under the guidance of senior data scientists
• Assist in evaluating time series data from well control equipment and contribute to predictive maintenance models
• Apply physics-based and data-driven models to field and test data, learning to account for noise and real-world test conditions
• Identify trends, anomalies, and patterns in operational data, and help build dashboards and KPIs for internal teams and clients
• Help prepare and present findings to colleagues and stakeholders
• Contribute to technical documentation and, as you develop, to publications, conference presentations, and patent work

Qualifications

What you bring

• A bachelor's degree (completed or expected within six months) in Petroleum, Mechanical, or another Engineering discipline, or in Mathematics, Statistics, Computer Science, Physics, or a related field
• A foundation in statistics, such as regression, probability distributions, and sampling
• Some experience with Python, R, or MATLAB from coursework, internships, or personal projects
• No professional experience required

Bonus points for

• Coursework, internships, or field experience in oil and gas, especially drilling, completions, or well integrity
• Familiarity with well barrier concepts or standards like NORSOK D-010, ISO 16530, API RP 90, or API Standard 53
• Experience with sensor or time series data from instrumented equipment or lab testing
• Exposure to machine learning methods and model validation
• Familiarity with Azure or another cloud platform, and with Git
• Technical writing experience, such as a thesis or capstone report

Additional Information

All your information will be kept confidential according to EEO guidelines.