Graduate Intern - Modeling and Data Science
About The Position
The Modeling and Data Science Graduate Level Intern will help advance practical engineering and data solutions for filtration research and product development. Working with the Modeling and Data Science team, the intern will gain hands-on experience across engineering simulation, software development, data engineering, and data science while developing digital engineering capabilities to accelerate innovation and product development at Donaldson. The internship program offers meaningful, hands-on experience in a collaborative industry environment through real-world projects, mentorship, and development opportunities. The role requires an on-site schedule at Donaldson’s Bloomington, Minnesota facility and may involve up to 5% travel. The position is overtime eligible. The hourly pay rate is $29.00–$32.00, depending on projected undergraduate graduation date, educational degree in progress, and major of study at the time of hire. Relocation assistance and immigration sponsorship are not available. Applicants must be legally authorized to work in the United States without current or future sponsorship, and must meet the stated U.S.-person requirement.
Requirements
- Currently pursuing a graduate degree in mechanical engineering, aerospace engineering, computer science, data science, data engineering, applied mathematics, or a related technical field.
- Coursework or project experience using Python for data analysis, numerical methods, machine learning, scientific computing, or application development.
- Experience working with technical datasets and communicating methods and results through written documentation or presentations.
- Must be a U.S. person: U.S. citizen, U.S. permanent resident, political asylee, or refugee.
- Must be legally authorized to work in the United States without the need for current or future immigration sponsorship.
Nice To Haves
- Graduate-level study or research experience in computational fluid dynamics, machine learning, scientific computing, or data engineering.
- Experience with deep-learning methods for spatial or high-dimensional data, including designing neural network architectures and training models using structured datasets.
- Experience with CFD software and flow-field data, including pressure, velocity, pressure-drop, or particle-transport results.
- Experience with reduced-order modeling, surrogate modeling, regression, validation, uncertainty analysis, or model-performance metrics.
- Experience with SQL, Snowflake or another cloud data warehouse, Streamlit, data validation, and layered data pipelines.
- Experience with CAD, parameterizing geometry, 3D scanning, or scan-to-CAD workflows.
- Familiarity with Git, software architecture, or AI-assisted development tools such as GitHub Copilot.
- Ability to gather requirements from engineers or laboratory users and convert them into a clear technical scope.
- Strong problem-solving, technical communication, and collaboration skills, and ability to work through an open-ended development problem.
Responsibilities
- Own a scoped technical project from problem definition through development and final recommendations.
- Build and evaluate Python-based engineering or data-science workflows using version-controlled, reproducible methods.
- Prepare, clean, validate, and analyze simulation or laboratory datasets, documenting data-quality issues and assumptions.
- Develop and test models or applications, such as deep-learning surrogates, reduced-order models, data-ingestion tools, or parameterized geometry workflows.
- Develop a parameterized geometry workflow for simulation setup, simulation execution, and results evaluation.
- Compare simulation results, laboratory results, or baseline engineering methods using appropriate technical metrics.
- Collaborate with simulation engineers, data scientists, and subject-matter experts to interpret practical requirements.
- Document architecture, methods, assumptions, and recommended next steps so the work can be extended after the internship.
- Provide progress updates, incorporate technical feedback, and communicate findings to technical and non-technical stakeholders.
- Follow Donaldson requirements for data access and security.
Benefits
- Retirement plan (401k).
- Paid time away, including sick and safe time for Minnesota employees.
- Employee assistance program.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
