Data Scientist – Product Safety Data Analytics

• Develop and standardize best practices for continuous monitoring of emerging safety issues
• Strengthen data-analytics support for safety investigations through improved methods, automated tools, and feedback loops
• Analyze signals, patterns, and trends in large and complex data sets to identify potential safety issues
• Support anomaly detection, diagnostics, prognostics, and root cause analysis for safety-related topics
• Design, build, and maintain repeatable analytical workflows using Python, SQL/Spark, Databricks, and related tools
• Identify automation opportunities and implement solutions using custom software, reusable code, data pipelines, and off-the-shelf technologies
• Prepare visualizations, summaries, and presentations for technical and non-technical audiences, including senior leadership
• Communicate assumptions, methods, limitations, and findings to support decision-making
• Build knowledge of vehicle safety technologies, their design intent and function, and intended field performance
• Work closely with business partners to understand challenges and needs, perform analyses, improve monitoring methods, and automate workflows

• 3+ years of work experience in applied statistics, analytics, engineering, data science, or a related field
• Bachelor’s degree in Applied Statistics, Mathematics, Econometrics, Computer Science, Operations Research, or a related quantitative discipline
• Proficiency in statistical data analysis, including outlier detection, time series analysis, categorical data analysis, multivariate analysis, sampling design, or analysis of variance
• Experience analyzing structured and/or unstructured data, including text or other sources requiring data-mining techniques
• Proficiency in Python and SQL/Spark
• Ability to develop clear, reusable, and maintainable analytical code
• Knowledge of statistical graphics and experience with Power BI and Tableau
• Experience with Databricks, data pipelines, data preprocessing workflows, and automation of recurring analytical processes
• Ability to communicate results and methodologies effectively, including presentation to senior leadership
• Strong work ethic, drive for results, and ability to work effectively in an ambiguous environment
• Understanding of vehicle safety technologies, including design intent, function, and intended field performance
• GM does not provide immigration-related sponsorship; candidates must not require GM immigration sponsorship now or in the future
• Willingness to travel less than 25%

Demonstrates expertise in statistical data analysis, including proficiency in Python and SQL/Spark for developing analytical workflows. Capable of communicating complex findings effectively to both technical and non-technical audiences, with a strong understanding of vehicle safety technologies.

• Statistical Data Analysis
• Python Programming
• SQL/Spark Proficiency
• Data Visualization with Power BI and Tableau
• Automation of Analytical Processes

• Applied Statistics
• Data Analysis
• Outlier Detection
• Time Series Analysis
• Multivariate Analysis
• Data Mining Techniques
• Analytical Code Development
• Data Preprocessing Workflows
• Root Cause Analysis
• Anomaly Detection

• Effective Communication
• Strong Work Ethic
• Drive for Results
• Ability to Work in Ambiguous Environments

• Vehicle Safety Technologies
• Safety Investigations
• Continuous Monitoring
• Feedback Loops
• Analytical Workflows

• Databricks
• Power BI
• Tableau
• Data Pipelines
• Automated Tools