Co-op: Engineering, Data Science (Fall 2026)

Who We Are

The Complete Vehicle Features, Analysis, and Simulation Team resides within the Complete Vehicle (CV) organization at Volvo Group North America. Our mission is to be the Voice of the Customer and to build confidence that our products work for our customers through comprehensive verification and validation. CV‑FAST brings together feature ownership, engineering analysis, simulation, and data science to ensure vehicle features are robust, balanced, and verified and validated with the right methods at the right time. The team owns complete vehicle‑level feature performance, leveraging simulation, analytical data, physical testing, and digital verification strategies to front‑load learning, reduce late‑stage risk, and improve customer uptime. CV‑FAST works closely with Engineering, Test, Product Planning, Product Management, and Brands to enable data‑driven decisions across the full product lifecycle. Together with us, you will be part of a global and diverse team of highly skilled professionals. We have a strong culture based on our company values, which are central to our work.

We believe in a work environment where: 

• We constantly strive for outstanding Performance.
• We are obsessed with Customer Success.
• We initiate Change to stay ahead.
• We willingly place our Trust in each other.
• We have a huge Passion for what we do. 

What You will be doing

At Volvo Group, you will contribute to the transformation of our company, the transport industry, and society at large. As a Data Science Co‑op within the CV‑FAST (Complete Vehicle Features, Analysis & Simulation) team, you will help turn complex vehicle and engineering data into actionable insights that support data‑driven development across the product lifecycle. You will work with data generated from simulations, testing activities, and connected vehicles to support analysis, modeling, and decision‑making that improves product performance, efficiency, and customer value. 

Working closely with engineers in Analysis & Simulation, Feature Engineering, Testing, and Digital teams, you will contribute to building data pipelines, developing analytics and machine learning solutions, and enabling modern, digital workflows. You will support efforts to improve how we analyze, visualize, and leverage data—helping accelerate the shift toward simulation‑driven and data‑driven development practices across Complete Vehicle. 

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
• Impact you will have:
• Help improve the speed and quality of engineering decisions through better data and insights
• Enable more efficient verification & validation processes through data-driven approaches
• Contribute to Volvo’s broader digitalization and AI transformation within product development 

Who You Are

You are a motivated and curious student with a strong interest in data science, analytics, and emerging AI technologies. You have a customer‑focused mindset and are eager to apply your technical skills to solve real‑world engineering problems. You are comfortable working with data, learning new tools, and collaborating with cross‑functional teams to generate insights that improve product decisions. You are energized by digitalization and excited to leverage data, simulation, machine learning, and AI to drive early learning, reduce risk, and support objective, data‑driven engineering decisions. You are interested in exploring how modern AI tools can accelerate workflows, enhance analysis, and enable more efficient and scalable engineering processes. 

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 

Preferrred: 

• 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