Senior Data Scientist / AI Engineer – Petroleum Engineering Analytics

Role: Senior Data Scientist / AI Engineer – Petroleum Engineering Analytics

Location: Houston, TX (Onsite)

Experience: 10+ Years

Domain Requirement: Mandatory Petroleum Engineering / Oil & Gas Upstream Experience

Job Summary

We are seeking a highly skilled Data Scientist / AI Engineer with strong experience in Petroleum Engineering and Oil & Gas operations to develop advanced analytics, machine learning, and AI-driven solutions for subsurface, drilling, reservoir, production, and asset optimization initiatives.

The ideal candidate will bridge the gap between data science and petroleum engineering by leveraging AI/ML technologies to improve operational efficiency, production forecasting, reservoir performance, and decision-making.

Required Qualifications

Bachelor''''s or Master''''s degree in Petroleum Engineering, Data Science, Computer Science, Applied Mathematics, or related discipline

8+ years of experience in Data Science, Machine Learning, or AI

5+ years of hands-on Petroleum Engineering or Oil & Gas Upstream experience (Mandatory)

Strong understanding of

Reservoir Engineering

Production Engineering

Drilling Operations

Well Performance Analysis

Field Development Planning

Experience working with Oil & Gas datasets including

Well logs

Production data

Reservoir simulation data

Pressure and temperature datasets

SCADA and sensor data

Technical Skills

Data Science & AI

Python, R, SQL

Machine Learning (Regression, Classification, Clustering)

Deep Learning (TensorFlow, PyTorch)

Generative AI and LLMs

Predictive Modeling

Time Series Forecasting

Optimization Algorithms

Statistical Analysis

Data Engineering & Cloud

Databricks

Apache Spark

Azure, AWS, or Google Cloud Platform

Snowflake

Data Lake Architecture

MLOps, CI/CD

Visualization

Power BI

Tableau

Spotfire

Python Visualization Libraries

Key Responsibilities

Develop AI/ML models for

Production forecasting

Well performance optimization

Reservoir characterization

Drilling efficiency analysis

Predictive maintenance

Build data-driven solutions to improve oil recovery and reduce operational costs.

Analyze large-scale subsurface and production datasets.

Apply machine learning techniques for anomaly detection and operational risk assessment.

Develop predictive models for artificial lift optimization and production enhancement.

Partner with Petroleum Engineers, Geoscientists, Drilling Engineers, and Asset Teams.

Implement Generative AI solutions for knowledge management, operational workflows, and engineering data analysis.

Design and deploy scalable AI solutions on cloud platforms.

Establish best practices for data governance, model monitoring, and MLOps.

Preferred Experience

Experience with major Oil & Gas companies such as ExxonMobil, Chevron, ConocoPhillips, Shell, BP, Occidental, Halliburton, Baker Hughes, Schlumberger (SLB), or similar.

Experience with

Petrel

OFM

Harmony

OpenWorks

Kingdom

Eclipse Reservoir Simulator

Knowledge of Digital Oilfield initiatives.

Experience implementing AI/ML solutions for upstream exploration and production operations.

Nice to Have

PhD in Petroleum Engineering, Data Science, or AI-related field.

Certifications in Azure AI, AWS ML, Databricks, or Cloud Architecture.

Experience with GenAI, RAG frameworks, and engineering document intelligence solutions.