Data analyst connectivity

• Master’s degree in Engineering, Data Science, Computer Science, Statistics, or a related technical or scientific field.
• Programming in Python (PySpark) and SQL is a must, basic knowledge of other programming languages is required
• Experience in cloud computing, data analysis and signal processing is required
• Notion of version control system, database structures and modeling techniques
• Knowledge of Matlab, Power query and PowerBI is a plus
• Interest in AI and the latest trends and evolutions in data science is a plus

At Atlas Copco Group you will join an international and diverse environment with specialists from different disciplines. Our culture is rooted in Swedish values, which includes a family feeling, respect and diversity. We invest in our employees’ development and well-being, and we provide a flexible work-life balance. With our inclusive and caring environment, you get the support and inspiration you need to grow. Here, your ideas are embraced, and you never stop learning.

You will have a comprehensive onboarding program, including guidance by a personal godmother/godfather. You will also have access to global job opportunities, as part of the Atlas Copco Group. We offer an interesting compensation and benefits package, including health insurance, paid leave and retirement benefits.

Did you know that the solutions we develop are key part of most industries? We’re everywhere! Working with us means that you can make an impact towards a sustainable future. Here, your ideas are embraced, you never stop learning, and you can be part of the solution for a better tomorrow.

Join us and make the difference.

Your role

“Data mining” is a trend you can’t miss these days. The use of data is becoming more and more standard in different domains like product design or decision making. Your role is to support other teams with your data analyses skills. Your focus point will be on “connectivity” data, but the requests can be very diverse. Many of our products are connected to the cloud, most of our products have digital twins, all our designs are created in a digital environment. There are plenty of opportunities to find relations, correlations, and influences to improve our products, processes or reporting tools. The knowledge and learnings are shared with the product development teams or other stakeholders like the service division or managment

Some examples:

• Could we improve the quality of our machines by standardizing on specific items that appear to be more reliable than others?
• What is a typical operating regime for a certain type of machines?
• Are our machines performing as expected?
• Do we get a lot of safety warning due to a clogged filter from a specific supplier?
• At which average outlet pressure do our machines operate at 1000m above sea level?