Göteborg, Västra Götalands län
Job Summary
VCC Fieldglass ID 1959 -
Measurement Data Analyst – Automotive Vehicle Testing
About the Role
We are looking for a skilled Measurement Data Analyst to support vehicle-level testing and validation activities within our automotive engineering organization. You will play a key role in transforming raw measurement data from vehicle tests (road, track, and simulation environments) into actionable insights that drive product quality, performance, and robustness.
This role is central to multi-functional testing (MFT) and data-driven validation , enabling cross-functional teams to understand vehicle behaviour under real-world and scenario-based conditions.
Key Responsibilities
Key Responsibilities
Data Analysis & Interpretation
Analyse measurement data from vehicle tests (e.g., CAN, Ethernet, sensor data, logging systems)
Process large datasets from SIL, HIL, VIL, and physical test drives
Identify trends, anomalies, and correlations across vehicle functions
KPI & Performance Evaluation
Define, calculate, and track vehicle-level KPIs/KPOIs (e.g., energy efficiency, drivability, thermal performance, ADAS behaviour)
Support scenario-based performance evaluation (e.g., urban drive cycles, highway, edge cases)
Develop automated pipelines for KPI extraction and reporting
Root Cause & Fault Analysis
Investigate deviations and failures observed during testing
Correlate signals across multiple ECUs and domains (powertrain, chassis, ADAS, infotainment)
Support fault injection analysis and robustness validation
Testing & Validation Support
Collaborate with test engineers to define measurement strategies and logging configurations
Ensure data quality, synchronization, and traceability
Support preparation and analysis of multi-functional test campaigns
Reporting & Visualization
Create clear, stakeholder-specific reports (engineering, project management, leadership)
Develop dashboards and visualizations for test results
Present insights and recommendations in a structured and concise manner
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Required Qualifications
Bachelor’s or Master’s degree in Electrical Engineering, Automotive Engineering, Data Science, or similar
3+ years of experience in automotive testing, measurement data analysis, or validation
Strong experience with:
Data analysis tools: Python (pandas, numpy), MATLAB, or similar
Measurement/logging tools: CANoe, CANalyzer, INCA, ETAS, or equivalent
Good understanding of:
Vehicle architectures and ECU communication (CAN, LIN, Ethernet)
Automotive testing frameworks (V-cycle, ASPICE, ISO 26262 awareness)
Skill Requirements
Skills
Preferred Qualifications
Experience with:
Scenario-based and multi-functional testing (MFT)
EV-specific analysis (battery, energy consumption, thermal behavior)
ADAS/AD data analysis and sensor fusion validation
Familiarity with:
Big data platforms or cloud-based analytics
Automation of data pipelines and test analysis workflows
Experience working in cross-functional, agile teams
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Key Competencies
Strong analytical and problem-solving skills
Ability to handle complex, multi-domain datasets
Structured communication tailored to different stakeholders
High attention to detail with focus on data quality and traceability
Proactive and collaborative mindset
Other Requirements
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