Join us and be a pioneer for a green transport revolution.
Automotive Cells Company (ACC) is one of Europe’s newest and most exciting high-tech companies. Backed by Saft-Total, Stellantis and Mercedes-Benz, ACC is set to power the future of the automotive industry by innovating in battery technology.
We aim to produce sustainable, affordable, high-capacity, longer-life batteries as a cleaner alternative to current energy sources. We have created an R&D center and new state-of-the art facility in Nouvelle Aquitaine, France, and we are building gigafactories in Germany and Italy, in addition to the one already built in Hauts de France.
We need a range of skilled and agile people to bring our vision to life, especially in the areas of industrialization, mechanical design, testing/prototyping and any other function of a new-born company. If you’re looking to take your career further than you imagined, if you’re passionate about creating cleaner transport, we’d like to hear from you.
Our core Values are : Pioneering Spirit, Fast & Agile, Excellence, Greener & Cleaner !
Accelerating sustainable mobility for all.
Your missions :
Join our dynamic team as a Data Analyst Intern, where you will play a pivotal role in developing PowerBI dashboards for all business lines within our manufacturing enterprise. Your mission will extend to delivering ad hoc exploratory analyses utilizing data analysis techniques and statistical methods. These analyses are crucial for investigating business line operations and driving strategic insights.
Your responsibilities :
- Design and develop intuitive PowerBI dashboards to visualize key metrics across various business lines.
- Conduct exploratory data analysis to uncover trends, patterns, and insights within business operations.
- Deliver exploratory data analysis using statistical methods to validate findings and support business line investigations.
- Collaborate with cross-functional teams to understand data needs and deliver actionable insights.
- Present findings to stakeholders, providing recommendations to inform decision-making processes.