Junior Data Scientist, Petroleum Engineering & Well Integrity

DataJobs; Houston (TX); On-site; USD 65,000 - 90,000; Full time

Job summary

IPT Global in Houston, TX is seeking a Junior Data Scientist to help verify well safety through data-driven insights. This onsite role combines analysis of well integrity data with model development and dashboard work, guided by senior data scientists and partnered stakeholders.

You’ll work on time series from well control equipment, apply physics-based and data-driven methods, and help build dashboards and KPIs for internal teams and clients.

Qualifications

• Formal education in statistics, regression, distributions, and sampling.
• Background in related engineering or quantitative fields as listed.
• Proficiency with Python, R, or MATLAB through coursework or projects.

Responsibilities

• Analyze well barrier datasets under supervision and contribute to models.
• Evaluate time series from control equipment and support predictive maintenance.
• Apply physics-based and data-driven approaches to field data and tests.
• Identify trends and KPIs; help build dashboards for teams and clients.
• Prepare findings for colleagues and stakeholders.
• Contribute to technical documentation and publications as opportunities arise.

Skills

Time series

Regression

Statistics

Python

R

MATLAB

Education

Bachelor's degree in engineering or quantitative field

Petroleum

Mechanical

Math/CS/Physics

Tools

Azure

Git

Job description

Build well-integrity insights that support safer operations. IPT Global is hiring an early-career Junior Data Scientist to help verify well safety through data-driven well integrity solutions. This onsite role in Houston, TX combines analysis of well barrier assurance data with model development and dashboard work, guided by senior data scientists and partnered stakeholders.

What you’ll do

• Support analysis of well barrier assurance and verification datasets under the guidance of senior data scientists.
• Assist in evaluating time series from well control equipment and contribute to predictive maintenance models.
• Apply physics-based and data-driven approaches to field and test data, learning how to account for noise and real-world test conditions.
• Identify trends, anomalies, and recurring 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, with growth opportunities that may include support for publications, conference presentations, and patent-related work.

What you bring

• A bachelor’s degree (completed or expected within six months) in a related engineering or quantitative field.
• Degree background that fits at least one of the following: Petroleum, Mechanical, or another Engineering discipline, or Mathematics, Statistics, Computer Science, Physics, or a related field.
• A foundation in statistics, including regression, probability distributions, and sampling.
• Some experience with Python, R, or MATLAB gained through coursework, internships, or personal projects.
• No professional experience required.

Tools you’ll work with

• Python, R, MATLAB
• Azure
• Git

Bonus points

• Coursework, internships, or field experience in oil and gas, especially drilling, completions, or well integrity.
• Familiarity with well barrier concepts or standards such as NORSOK D-010, ISO 16530, API RP 90, or API Standard 53.
• Experience working 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 Git.
• Technical writing experience, such as a thesis or capstone report.

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