Data Scientist​/Data Engineer – ADAS IRC

Function

Data Analytics & Business Intelligence (BI)

5-10 years

Sweden - Gothenburg

ADAS, Automotive, Data Engineer, Data Science, Python

We are looking for a Data Scientist / Data Engineer to support the client’s ADAS organization. This role sits at the intersection of data engineering and applied data science, working with large-scale sensor and vehicle data used to develop, validate, and improve ADAS functions (e.g., collision avoidance, lane keeping, adaptive cruise control, sensor fusion). The ideal candidate combines strong technical data skills with the interpersonal drive needed to work across multiple engineering teams and extract the right requirements and context.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Electrical Engineering, or a related field.
• 3+ years of experience in data engineering or data science roles, ideally within automotive or another safety-relevant industry.
• Demonstrated experience working with ADAS-related data (sensor data, perception outputs, vehicle logs) or strong interest and transferable experience from adjacent domains (robotics, autonomous systems).
• Strong proficiency in Python and standard data engineering tool chains; hands-on experience with Git/Git Hub for version control and collaborative development.
• Experience with large-scale data processing frameworks (e.g., Spark, Pandas, SQL-based data warehouses).
• Familiarity with data pipeline orchestration tools (e.g., Airflow) is a plus.
• Understanding of automotive data standards (CAN, DBC files, AUTOSAR data concepts) is a strong plus.

• High drive and initiative - comfortable proactively reaching out across departments (ADAS function teams, test/validation, software, systems engineering) to gather context and clarify ambiguous requirements.
• Strong communication skills; able to translate between technical data language and functional/engineering language.
• Curious, self-directed problem-solver who takes ownership of data quality and pipeline reliability end-to-end.
• Comfortable operating in a fast-paced, cross-functional environment with evolving priorities.

• Design, build, and maintain data pipelines for ingesting, processing, and structuring large volumes of ADAS sensor and test data (camera, radar, lidar, CAN bus logs).
• Apply data science methods to analyze vehicle and sensor datasets, supporting feature development, algorithm validation, and performance benchmarking of ADAS functions.
• Collaborate with ADAS function owners, test engineers, and software teams to translate development and validation needs into data requirements.
• Develop and maintain reusable Python-based tools and scripts for data extraction, transformation, and analysis, version-controlled via Git Hub.
• Support root-cause analysis of ADAS performance issues using data-driven investigation.
• Contribute to data quality frameworks, labeling standards, and metadata management specific to ADAS datasets.
• Present findings and data insights clearly to both technical and non-technical stakeholders.

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. We are dedicated to providing equal opportunities for all individuals, fostering an inclusive and empowering work environment.

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