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.