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Greensboro, NC

Internship

Onsite

$17/hr - $46/hr

Intern

Volvo Group develops sustainable transport and infrastructure solutions through collaborative teams and next-generation technologies. The Data Science Co-op will analyze simulation, testing, and connected-vehicle data, develop data pipelines and machine learning solutions, and create analytics tools that support data-driven engineering, product validation, and digitalization.

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Responsibilities

Work with engineers and data scientists to analyze simulation, test, and vehicle data to identify trends, anomalies, and improvement opportunities
Clean, transform, and structure raw datasets to make them usable for analysis and modeling
Develop and maintain data pipelines, scripts, and notebooks to automate repetitive analysis tasks
Create dashboards and visualizations to communicate key insights to engineering teams and stakeholders
Use AI-assisted tools to accelerate data exploration, generate code, and improve productivity
Support the validation of data and models to ensure accuracy, robustness, and reproducibility
Participate in team standups, technical discussions, and cross-functional collaboration to align on priorities and deliverables
Build predictive models using vehicle and test data to identify potential performance issues or trends
Develop AI-assisted tools or workflows (e.g., automated reports, insight generation, or data analysis pipelines) to improve engineering efficiency
Analyze data from vehicle simulations and physical testing to support correlation and improve product validation strategies
Support the development of digital twin or simulation-driven analytics capabilities by ensuring high-quality, structured data inputs
Create or enhance Power BI or Streamlit applications that enable engineers to explore and interact with data more effectively
Contribute to projects that automate or modernize engineering processes, reducing manual work and improving consistency
Experiment with machine learning or generative AI techniques to improve how insights are generated and communicated

Qualification

Required

Currently enrolled in a Bachelor's or Master's program in Data Science, Computer Science, Engineering, Statistics, or a related field
Applicants must have a minimum cumulative grade point average of 2.75
Co-ops are not enrolled in academic courses during their co-op rotation and may work up to 40 hours per week
Hands‑on experience with programming for data analysis (e.g., Python, SQL)
Basic understanding of statistics, data analysis, and machine learning concepts
Familiarity with AI/ML workflows, including data preparation, feature engineering, model training, and evaluation
Exposure to Generative AI or AI-assisted tools (e.g., using AI for coding, analysis, or automation)
Experience working with datasets (cleaning, structuring, analyzing data)
Strong problem‑solving skills and ability to communicate findings clearly
Ability to validate outputs and ensure data quality, accuracy, and reproducibility
Ability to work collaboratively in a team environment and learn in a fast‑paced setting

Preferred

Experience with data visualization tools (e.g., Power BI, matplotlib, plotly)
Exposure to machine learning libraries (e.g., scikit‑learn, TensorFlow, PyTorch)
Familiarity with modern AI concepts (e.g., prompt engineering, embeddings, or retrieval‑based approaches)
Experience building AI-assisted workflows or lightweight tools (automation scripts, dashboards, or applications)
Familiarity with data pipelines, automation, or scripting workflows
Experience working with engineering, simulation, or test data
Interest in automotive, transportation, or heavy‑duty vehicle systems
Exposure to cloud platforms, databases, or big data tools
Experience contributing to projects involving AI, analytics, automation, or dashboards