For our client Volvo Cars, we are looking for a Data Scientist.

The Vehicle Propulsion and Energy Data Analytics team analyzes data related to high voltage batteries, vehicle charging, and electric drive to gain insight into how our products work and ensure the customer experience gets better every day. Your contribution will focus specifically on high voltage batteries, improving the quality of our cars by bringing better and faster feedback to our developers and product designers.

We are a tight-knit group with a friendly and enthusiastic team spirit . We have many clear, concrete, and inspiring opportunities within our team and organization to apply your data science skills.

What You’ll Do

You will perform statistical analyses of fleet data to help stakeholders gain better insight into vehicle behavior. You will use machine learning and statistics to make predictive models for vehicle systems, and visualization techniques to present complex results to stakeholders in a clear and understandable way.

You will also write code in Python, review and give feedback on your colleagues’ code, construct dashboards, and enable automated, continuous feedback on software and hardware quality.

Who are You?

We love what we do, and we think it’s important that you do too. You should be eager to learn and develop your knowledge and skillset, and support others with their personal and professional growth as well. You must be open to ideas from others, even when they may be less experienced than you – we value both ambition and humility!

Key Competencies

•Exploratory and confirmatory data analysis

•Pyspark, SQL, and ETL pipelines

•Visualization tools (specifically matplotlib and seaborn)

•Ability to write clean, readable code in Python that follows best practices

•Scientific computing libraries (e.g. numpy, scipy, pandas, polars)

•Basic proficiency with git

•Computing platforms such as Databricks and Jupyter

Meritorious

•Experience within the automotive and diagnostics domain

•Experience in high voltage battery design, analytics, assembly, or repair

•Machine learning and statistical modeling

•Developing software with Linux systems

•Cloud technologies such as Azure and AWS