Data Scientist (Oil and Gas)

No sponsorship is available now or in the future. 3 days onsite in Houston,TX (Downtown)

Title:Data Scientist (Oil and Gas)

Location: Houston,TX - Hybrid 3 days in office

Type of Role: Full time

Description

We are seeking a Data Scientist with strong downstream refining experience to drive data-

driven insights across refinery operations, economics, and reliability. This role partners

closely with process engineers, operations, planning, maintenance, and commercial teams

to optimize refinery performance using advanced analytics, machine learning, and domain-

informed modeling.

You’ll work on high-impact problems such as yield optimization, energy efficiency, unit

reliability, predictive maintenance, and margin improvement—turning complex refinery data

into actionable intelligence.

Analytics & Modeling

 Develop, validate, and deploy statistical, ML, and optimization models for refining

operations

 Build models supporting:

o Unit performance optimization (e.g., CDU/VDU, hydrotreating, cracking)

o Energy efficiency and utilities optimization

o Yield and cut-point optimization

o Predictive maintenance and reliability analytics

o Fouling, corrosion, and anomaly detection

o Apply time-series analysis to high-frequency plant data (DCS, historian)

Refining Domain Collaboration

 Partner with process engineers, operations, maintenance, and planning

teams to translate refinery problems into analytical solutions

 Incorporate first-principles knowledge (mass & energy balances, constraints,

process limits) into data models

 Interpret model results in the context of refinery economics, safety, and operability

Communication Impact

 Clearly communicate insights to technical and non-technical stakeholders

 Quantify business impact (margin improvement, energy reduction, reliability gain

Responsibility

 Bachelor’s or Master’s degree in Data Science, Chemical Engineering, Applied

Mathematics, Statistics, or related field

 3–8+ years of experience applying data science in downstream refining or closely

related process industries

 Strong proficiency in Python or R for data analysis and modeling

 Experience with time-series data and industrial process data

 Solid understanding of refining processes and unit operations

 Experience working with historians (PI), SQL databases, and unstructured data