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Data Scientist Intern; PhD level

Job in Hazelwood, St. Louis city, Missouri, 63042, USA
Listing for: Lubrizol Corporation
Apprenticeship/Internship position
Listed on 2026-06-18
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Analyst
Salary/Wage Range or Industry Benchmark: 10000 - 60000 USD Yearly USD 10000.00 60000.00 YEAR
Job Description & How to Apply Below
Position: Data Scientist Intern (PhD level)
Location: Hazelwood

Data Scientist/Statistician Intern (PhD Level)

Unleash Your Potential. At Lubrizol we're transforming the chemical industry and looking for exceptional talent to join us on this journey. If you are ready to join an international company with talent around the world, and want to make a real impact, we want you on our team.

What You'll Do:

The empowered and agile Data Science & Statistics team is charged with creating analytics systems that enable highly effective product development via virtual experimentation, optimization and knowledge discovery. In addition, the team provides data science consulting services to the Lubrizol technical community throughout the world. You'll collaborate with a diverse group of passionate individuals to deliver sustainable solutions to advance mobility, improve wellbeing and enhance modern life.

Potential

Projects (depending on intern skills and current Lubrizol needs):
  • Create predictive models by mining complex data for critical formulating or testing insights
  • Implement and assess algorithms in R and Python (SAS, JMP, or C#/C++, optional)
  • Research, develop, and operationalize new statistical, machine learning and/or optimization methods
  • Implement and improve forecasting algorithms
  • Investigate applications of Cheminformatics modelling
  • Investigate active learning for process optimization
  • Scheduling and inventory optimization
  • Accelerate process and product development cycle using emerging AI methods (such as LLM, RAG, Agentic AI)
Previous Intern Projects Include:
  • Predictive modeling using Bayesian and machine learning methods
  • R/Shiny tool development to enable model predictions and formulation optimization
  • Creation of an interactive visualization tool for monitoring predictive models
  • Development of a bootstrap procedure for a hypothesis test
  • Multitask learning (transfer learning) using co-regionalized Gaussian Processes
  • Multivariate variable selection approach using Variational Bayes
  • Multi-objective optimization using genetic algorithms
  • Survival modeling using bagged Cox proportional hazards regression trees
  • Bootstrap variance estimation for complex nonlinear models
Requirements:
  • Enrolled in a PhD program such as statistics, data science, machine learning, or in chemistry/chemical engineering with data science skills
  • Dual degree students (e.g., statistics/data science and chemistry, chemical engineering, computational chemistry, etc.) are encouraged to apply
Skills That Make a Difference:
  • Significant coursework in one or more out of:
    • Predictive modeling
    • Bayesian approaches
    • Optimization
  • Able to efficiently manipulate, process, and analyse data of various modalities, including numerical, image, text, and beyond
  • Advanced programming skills and exposure to data query languages
  • Interest and experience in advanced statistical and machine learning methodology (PhD level)
  • Curiosity, creativity, initiative, and autonomy
Perks and Rewards That Inspire:
  • Competitive hourly wage with tenure-based raises
  • Paid holidays within your work period
  • Subsidized on-site restaurant
  • Free car parking

Start and end dates are flexible dependent on your course structure and availability; internships typically last for 12-16 weeks.

Lubrizol is an equal opportunity employer. We are committed to providing an environment where every employee can be the best they can be, no matter their race, colour, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic.

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