Data Scientist

Lets introduce ourselves

Virtual Hardware Methodologies and Strategy is responsible for securing PMTI (Process Methods Tools & Information) for virtual hardware development at Volvo Cars. The primary focus is CAD alongside design-related CAE and PLM business needs.
A key part of our mission is driving the transformation toward the next-generation development environment with 3DEXPERIENCE (3Dx) as a central parallel we are building future capabilities in AI-driven product development focusing on generative AI augmented engineering and agentic models to accelerate hardware development.

This role is central to advancing AI-driven hardware development at Volvo Cars. By combining business understanding data-driven thinking and modern AI capabilities you will help enable better engineer support faster access to information more intelligent workflows and increased development speed.

The role is also a key enabler in translating the potential of 3Dx our future information environment and enterprise AI capabilities into tangible impact in development work.

What youll do

We are looking for a Data Scientist to drive our Generative AI strategy for virtual hardware developmentcombining strategic direction with hands-on development of high-impact use cases. You will analyze data to draw insights patterns and conclusions that will enable the business to improve their products services processes or to develop new strategies.
You will work closely with the Unified Hardware Factory (UHWF) and key stakeholders to identify prioritize and implement AI-driven solutions that create real business value. This includes developing use cases within the 3DEXPERIENCE platform and contributing to a broader enterprise AI capability for hardware development.
This role is ideal for someone who can bridge data technology and business translating needs into practical AI solutions that improve efficiency quality and engineering workflows.

Main responsibilities:
Define and drive the Generative AI strategy for virtual hardware development
Design develop and deploy AI-powered tools with clear business value
Identify and prioritize AI use cases together with UHWF and stakeholders
Translate business needs into use cases experiments and implementations
Develop solutions within 3DEXPERIENCE and across enterprise AI capabilities
Enable scalable AI by shaping data information and ways of working
Collaborate with CAD CAE PLM and methodology experts to ensure adoption
Evaluate opportunities risks and maturity of AI technologies

What youll bring

We believe you hold a degree in Data Science AI/ML Computer Science Engineering or a related field and have experience with machine learning generative AI or advanced analytics. You are capable of translating technology into clear business value and have experience developing data-driven use cases in complex environments. You also have proficiency in relevant programming languages a solid understanding of data information models and system landscapes and strong collaboration and communication skills across both technical and business stakeholders.

It is considered meritorious if you have experience in automotive or other complex product development environments along with knowledge of CAD CAE PLM MBSE or digital thread. Experience applying AI in engineering contexts as well as familiarity with 3DEXPERIENCE or similar enterprise platforms is highly valued. Additional strengths include working with augmented engineering AI-driven decision support or agents and driving innovation in cross-functional settings.

To succeed in this role you are strategic and able to identify long-term opportunities while building clear direction. You are pragmatic and focused on delivering real business value combined with a curious and forward-looking mindset regarding how AI is transforming engineering. You collaborate effectively across functions building trust with both technical and business stakeholders and you are self-driven with the ability to turn ideas into concrete actions. You are also structured able to balance exploratory work with implementation and delivery.