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Chemical Engineering Data Science Jobs in California

Sandisk

Senior Staff Data Science Engineer

Milpitas, CA · On-site

$172K - $286K/yr

This role requires deep expertise in machine learning engineering, data science methodologies, and large-scale AI systems , combined with strong domain intuition in semiconductor/NAND environments

ODORZX INC.

Chemical Engineer

Los Angeles, CA · On-site

Solid understanding of chemical engineering principles and processes * Proficiency in using industry-standard software for data analysis and simulation * Strong analytical and problem-solving skills

Find Data Science

Data Scientist

San Francisco, CA · On-site

... Science, Mathematics, Statistics, or a related field. * Proven experience as a Data Scientist or similar role, preferably in a fast-paced environment. * Strong proficiency in programming languages ...

ODORZX INC.

Chemical Engineer

Los Angeles, CA · On-site

Solid understanding of chemical engineering principles and processes * Proficiency in using industry-standard software for data analysis and simulation * Strong analytical and problem-solving skills

ODORZX INC.

Chemical Engineer

Los Angeles, CA · On-site

Solid understanding of chemical engineering principles and processes * Proficiency in using industry-standard software for data analysis and simulation * Strong analytical and problem-solving skills

The Aerospace Corporation

Data Scientist

El Segundo, CA · On-site

$95K - $142K/yr

The Data Science and Artificial Intelligence Department (DSAID)seeksa creative and enthusiastic Machine Learning Engineerto join a diverse team of engineers, data scientists, and programmers with a ...

SPACE EXPLORATION TECHNOLOGIES CORP

$100 - $125/hr

Overview SpaceX is seeking a CHEMICAL ENGINEER to join the Launch Pad Engineering Team in ... Present certification packages and engineering data to U.S. government agencies including NASA and ...

The Aerospace Corporation

Data Scientist

El Segundo, CA · On-site

$100 - $125/hr

The Data Science and Artificial Intelligence Department (DSAID) seeks a creative and enthusiastic Machine Learning Engineer to join a diverse team of engineers, data scientists, and programmers with ...

The Aerospace Corporation

Data Scientist

El Segundo, CA · On-site

$95K - $142K/yr

The Data Science and Artificial Intelligence Department (DSAID) seeks a creative and enthusiastic Machine Learning Engineer to join a diverse team of engineers, data scientists, and programmers with ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$134K - $161K/yr

Wehave multiple openings for a Data Science Engineer with a background in applied machine learning ... These positions are in the Computational Engineering Division (CED), within the Engineering ...

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All JobsChemical Engineering Data Science JobsChemical Engineering Data Science Jobs in California

Chemical Engineering Data Science information

See California salary details

$25K

$97.6K

$191.9K

How much do chemical engineering data science jobs pay per year?

As of Sep 8, 2026, the average yearly pay for chemical engineering data science in California is $97,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,961.00 and $136,112.00 per year, depending on experience, location, and employer.

What is a chemical engineering data science?

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 does a chemical engineering data science do?

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.

What are the key skills and qualifications needed to thrive in chemical engineering data science?

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.

Can a chemical engineering data scientist become a data scientist?

A chemical engineering data scientist can become a data scientist by expanding their skills in programming, statistics, and machine learning, which are essential for general data science roles. Their domain expertise can be an advantage in industries like energy, pharmaceuticals, or manufacturing, but they may need additional training or certifications in data science tools such as Python, R, or SQL. Transitioning often involves gaining experience with broader data analysis techniques and project management skills common in data science positions.

What are the most commonly searched types of Chemical Engineering Data Science jobs in California?

The most popular types of Chemical Engineering Data Science jobs in California are:

What are popular job titles related to Chemical Engineering Data Science jobs in California?

For Chemical Engineering Data Science jobs in California, the most frequently searched job titles are:

What job categories do people searching Chemical Engineering Data Science jobs in California look for?

The top searched job categories for Chemical Engineering Data Science jobs in California are:

What cities in California are hiring for Chemical Engineering Data Science jobs?

Cities in California with the most Chemical Engineering Data Science job openings:

Chemical Engineering Data Science jobs near you
Infographic showing various Chemical Engineering Data Science job openings in California as of August 2026, with employment types broken down into 75% Full Time, 10% Part Time, and 15% Contract. Highlights an 90% In-person, 4% Hybrid, and 6% Remote job distribution, with an average salary of $97,637 per year, or $46.9 per hour.

Job Title: Data Scientist - Contract jobs - San Jose, CA

Tech Mirrors

San Jose, CA • On-site

$150 - $200/hr

Other

Posted 9 days ago

Job description

Job Title: Data Scientist - 10+yrs-

San Jose, United States - onsite

client - Virtusa

Need only H1

Job Summary

We are looking for an experienced Data Scientist with strong hands-on expertise in Python, SQL, Statistical Analysis, Machine Learning, and Predictive Modeling. The candidate will work on end-to-end data science projects, from data preparation and feature engineering through model development, deployment, and performance monitoring.

Key Responsibilities

  • Develop predictive models and machine learning solutions using Python.
  • Perform statistical analysis and identify patterns and trends in data.
  • Work with structured and unstructured datasets.
  • Perform data cleaning, validation, transformation, and feature engineering.
  • Develop and optimize ML models using Scikit-learn, Pandas, and NumPy.
  • Deploy machine learning models into production.
  • Track experiments and maintain model documentation using MLflow, DVC, or Jupyter.
  • Ensure data quality, model accuracy, and performance.
  • Analyze results and translate technical findings into actionable business insights.
  • Work independently on projects from data discovery through deployment.
  • Collaborate with business and technical teams to solve data-driven problems.

Required Skills

  • Python - Mandatory
  • SQL - Mandatory
  • Data Science
  • Predictive Modeling
  • Statistical Analysis
  • Machine Learning
  • Scikit-learn
  • Pandas
  • NumPy
  • Feature Engineering
  • Data Integration
  • Model Deployment
  • Structured & Unstructured Data

Preferred Skills

  • MLflow
  • DVC
  • Jupyter
  • Model Monitoring
  • MLOps
  • Production Machine Learning
  • Data Visualization
  • Cloud platforms
  • Git

Primary Skills

  • Python | SQL | Data Science | Machine Learning | Predictive Modeling | Statistical Analysis | Scikit-learn | Pandas | NumPy

Secondary Skills

  • Feature Engineering | Data Integration | MLflow | DVC | Jupyter | Model Deployment | MLOps | Model Documentation

Ideal Candidate

The ideal candidate should have 4+ years of hands-on Data Science experience, with strong expertise in Python, SQL, predictive modeling, statistical analysis, and machine learning.

The candidate must be comfortable taking ML projects from data discovery and feature engineering through model development and production deployment.

Recruiter Screening - Must Have

Python + SQL + Machine Learning + Predictive Modeling + Statistical Analysis + Scikit-learn + Pandas/Num

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