Job Description

Data Scientist/Statistician Intern (MS/PhD)

Join Our Thriving Team at Lubrizol as a Data Scientist/Statistician Intern (MS/PhD). 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 delivers data science solutions for computer vision automation, Operations, and Supply Chain and offers 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.

What We're Looking For:

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)
• Collaborate with the data science team, as well as scientists and chemical engineers, to understand their needs and find creative solutions to meet those needs
• Deploy algorithms and create predictive models by mining complex visual data
• Research, develop, and operationalize new statistical, machine learning and/or optimization methods (PhD level)

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 (PhD level)
• Multivariate variable selection approach using Variational Bayes (PhD level)
• Multi-objective optimization using genetic algorithms (PhD level)
• Survival modeling using bagged Cox proportional hazards regression trees (PhD level)
• Bootstrap variance estimation for complex nonlinear models (PhD level)

Skills That Make a Difference:

• Enrolled in a Master's or PhD program such as statistics, data science, machine learning, or chemical engineering
• Dual degree students (e.g., statistics/data science and chemistry, chemical engineering, computational chemistry, etc.) are encouraged to apply
• Significant coursework in predictive modeling, Bayesian approaches, and optimization, deep learning, forecasting, multivariate data analysis, and/or generative AI
• Able to efficiently manipulate, process, and analyze 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:

• Preferred location of Wickliffe, OH or Deer Park, TX, but potential for remote work opportunity
• Housing and relocation assistance available for eligible students
• Competitive hourly wage
• Paid holidays within your work period

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