What are the responsibilities and job description for the Senior Data Scientist / AI Engineer – Petroleum Engineering Analytics position at Intake IT Solutions?
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.