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Chemical Engineering Data Science Jobs (NOW HIRING)

Valero

Data Science Specialist

San Antonio, TX

Mathematics, Engineering, Data Science or Computer Science or related field or equivalent. * 5 ... years of experience in programing & data mining. * Able and willing to work on-site, in-person at ...

Valero Energy

Data Science Specialist

San Antonio, TX · On-site

Mathematics, Engineering, Data Science or Computer Science or related field or equivalent. * 5+ ... years of experience in programing & data mining. * Able and willing to work on-site, in-person at ...

Buckman

Digital Innovation Engineer

Memphis, TN · On-site

$121K/yr

S. or equivalent experience in Computer Science, Chemical Engineering, Electrical Engineering ... Data Engineering - Relational and NoSQL data, Data visualization tools such as Power BI, streaming ...

Buckman

Digital Innovation Engineer

Memphis, TN

$121K/yr

S. or equivalent experience in Computer Science, Chemical Engineering, Electrical Engineering ... Data Engineering - Relational and NoSQL data, Data visualization tools such as Power BI, streaming ...

Buckman

Digital Innovation Engineer

Memphis, TN · On-site

$132K/yr

S. or equivalent experience in Computer Science, Chemical Engineering, Electrical Engineering ... Data Engineering - Relational and NoSQL data, Data visualization tools such as Power BI, streaming ...

Buckman

Digital Innovation Engineer

Memphis, TN · On-site

$132K/yr

S. or equivalent experience in Computer Science, Chemical Engineering, Electrical Engineering ... Data Engineering - Relational and NoSQL data, Data visualization tools such as Power BI, streaming ...

Buckman

Digital Innovation Engineer

Memphis, TN · On-site

$132K/yr

S. or equivalent experience in Computer Science, Chemical Engineering, Electrical Engineering ... Data Engineering - Relational and NoSQL data, Data visualization tools such as Power BI, streaming ...

Buckman

Digital Innovation Engineer

Memphis, TN

$132K/yr

S. or equivalent experience in Computer Science, Chemical Engineering, Electrical Engineering ... Data Engineering - Relational and NoSQL data, Data visualization tools such as Power BI, streaming ...

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All JobsChemical Engineering Data Science Jobs

Chemical Engineering Data Science information

What is a Chemical Engineering Data Science job?

A Chemical Engineering Data Science job combines chemical engineering principles with data science techniques to analyze and optimize chemical processes. Professionals in this field work with large datasets, machine learning models, and statistical methods to improve efficiency, reduce costs, and enhance safety in industries such as pharmaceuticals, energy, and materials. They may develop predictive models, conduct simulations, and implement AI-driven solutions to solve complex engineering challenges. This role requires expertise in programming, data analytics, and chemical process understanding to drive data-informed decision-making.

What are the key skills and qualifications needed to thrive in the Chemical Engineering Data Science position, and why are they important?

To succeed in Chemical Engineering Data Science, you need a strong background in chemical engineering principles, statistical analysis, and programming (usually with Python, R, or MATLAB), often supported by a degree in chemical engineering or data science. Familiarity with machine learning algorithms, process simulation software (like Aspen Plus or HYSYS), and data visualization tools is highly valuable, and certifications in data analytics or Six Sigma can be advantageous. Strong analytical thinking, problem-solving, and effective communication skills help you interpret data-driven insights and collaborate with multidisciplinary teams. These competencies are essential for solving complex engineering problems, optimizing processes, and delivering actionable results in data-intensive chemical industry settings.

What are the typical daily responsibilities of someone working in Chemical Engineering Data Science?

Professionals in Chemical Engineering Data Science typically spend their days collecting and cleaning process data, developing data models to predict or optimize chemical operations, and interpreting analytical results to improve production efficiency or product quality. They often use specialized software to simulate chemical processes and collaborate closely with engineers, plant operators, and IT professionals to implement data-driven solutions. Regular tasks may also include creating reports and data visualizations, troubleshooting data quality issues, and supporting digital transformation projects within manufacturing environments. The role is dynamic and requires continual learning as new tools and methodologies emerge, making strong communication skills and adaptability especially important.

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Chemical Engineering Data Science jobs near you
Infographic showing various Chemical Engineering Data Science job openings in the United States as of July 2026, with employment types broken down into 72% Full Time, 6% Part Time, and 22% Contract. Highlights an 89% In-person, and 11% Remote job distribution.
Data Scientist (Oil and Gas)

Data Scientist (Oil and Gas)

Sky Consulting Inc

Houston, TX • On-site

Full-time

Posted 27 days ago

Job description

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