Data Scientist - Safety Research

Who are we?
Volvo Cars is a company on a mission; to bring traditional car manufacturing into a connected, sustainable and smart future.
Since 1927, we have been a brand known for our commitment to safety, creating innovative cars that make life less complicated for our consumers. In 2010, we decided to transform our business, resulting in a totally new generation of cars and technologies, as well as steady growth and record sales. Today, we’re expanding our global footprint in Europe, China and the US, and we’re on the lookout for new talent.
We are constantly pushing our own skills and abilities to drive change in the automobile industry like never before. We are looking for innovative, committed people to join us in this endeavour and create safe, sustainable and connected cars. We believe in the power of people and will challenge and support you to reach your full potential. Join us and be part of Volvo Cars’ journey into the future.

The Data, Analytics and Artificial Intelligence team at Volvo Cars Safety Centre works in large part with real world safety data to understand and explain accident and injury causation mechanisms and, thus, laying foundations for future safety features and functions in upcoming car development programs. We provide our knowledge to our car programmes through data analysis and knowledge needed to help drive the engineering of world leading products. The work is performed in close collaboration with Volvo Cars digital organisation and relevant data analytics organisations that provides us the governance and digital infrastructure for retrieving and analysing real world data.
Position and Person Details

We are currently looking for a data scientist with excellent software development skills. Your primary focus will be to develop world class data analytics and AI products by applying scientifically established methods and techniques such as statistics, machine learning and deep learning. You shall develop these by following best practices and well accepted design principles in software engineering and machine learning operations (ML/AIOPS). In addition, you may have the opportunity to be involved in developing novel methods in data science with automotive safety as a focus area.

Main responsibilities
- Ability to map a business question to analytical context outlining the choice of methods and analytical subsets of data,
- Pre-processing of structured and unstructured data including cleansing and validating the quality and integrity of data in the analytical context,
- Enhancing data collection procedures to include all relevant information for developing analytic products. Ability to fuse multiple datasets in a given context,
- Implement appropriate statistical, machine learning and/or deep learning methods for appropriate business questions and relevant datasets,
- Develop and deploy data science products in the cloud or on-prem infrastructure,
- Communicate and collaborate with other parts of the company and ensure that best practices are used for designing and documenting solutions.

Required qualifications
- University degree in a quantitative discipline (e.g., but not limited to – Mathematics, Computer Science, Data Science, Natural Sciences, etc.) or equivalent work experience,
- Previous work experience in writing Ability to write high quality data science code in Python programming language. Proven track record and knowledge of best practices and standards in coding, familiarity with Python-based data processing and analysis libraries,
- Well versed with visualizing the insights in dashboards or similar solutions either off-the-shelf or Python-based frameworks,
- Significant experience in developing end-to-end Data Science software solutions,
- Experience with state-of-the-art data science and ML practices along with advanced knowledge of and experience with Python-based ML and DL libraries (particularly for ML) as well as version control (e.g., git and GitHub),
- Experience in developing scalable ML-based production systems in the cloud using multiple platforms such as Databricks and Azure,
- Familiarity and exposure to large language models and principles of generative AI,
- Fluent in English (written and verbal).

Meritorious competences
- Work experience with vehicle safety data and principles,
- Familiarity with ML-ops and cloud environments at Volvo Cars,
- Proven experience with Kubernetes and Docker,
- Knowledge of and interest in data engineering aspects and data pipelines
- Experience working with large scale text processing, classification and analysis methods.

Personal qualities
- Passion for data science and analysis,
- Structured way of working, and good documentation skills,
- A self-driven and result oriented team player,
- Willingness to learn and improve.