Product Safety Data Analytics – Data Analyst

General Motors • Warren, MI

6d • Hybrid

About The Position

About GM There’s never been a more exciting time to work at General Motors. To achieve our vision of Zero Crashes, Zero Emissions, and Zero Congestion, we need people who are passionate about creating safer, smarter, and more sustainable mobility solutions. About Product Safety Data Analytics (PSDA) Product Safety Data Analytics (PSDA) is a core part of GM’s safety ecosystem. PSDA supports safety decision-making by identifying potential emerging vehicle safety issues through the analysis, mining, and monitoring of large volumes of structured and unstructured data. The team works across customer complaints, engineering data, crash and field reports, vehicle telemetry, surveys, and research data to detect trends, assess risk, and deliver decision-ready insights to safety, engineering, and leadership stakeholders. The Role The Product Safety Data Analyst supports Global Vehicle Safety and related organizations by executing rigorous, unbiased data analyses that inform safety investigations and decisions. This role is primarily focused on data extraction, preparation, analysis, visualization, and communication. The analyst works closely with safety engineers, statisticians, and analytics partners to ensure analyses are accurate, timely, and clearly presented.

Requirements

• 3+ years of post-graduation experience in analytics, statistics, or a related field
• Bachelor’s degree in applied Statistics, Mathematics, Actuarial Science, or a related discipline
• Working knowledge of statistical techniques, including: Time series analysis Categorical data analysis Multivariate analysis Logistic regression Linear and non-linear modeling Outlier assessment / anomaly detection
• Strong proficiency in data visualization and charting
• Experience analyzing text or unstructured data using text mining, machine learning, or similar methods
• Proficiency with one or more programming or query languages (e.g., SQL, Python, R)
• Experience with data preparation, cleaning, rationalization, and processing
• Ability to independently manage a high-volume workload
• Comfortable working in ambiguity and responding to unplanned requests
• Strong written and verbal communication skills
• Demonstrated continuous-learning mindset
• Data & Query: SQL; Databricks
• Programming: Python; PySpark (preferred)
• Analytics & BI: Power BI, Tableau; Excel

Nice To Haves

• Experience working with vehicle diagnostics, telemetry, or connected-vehicle data
• Familiarity with interpreting diagnostic signals, fault codes, and time-series vehicle data in an analytics or safety context
• Working knowledge of vehicle safety systems, vehicle components, and field performance
• AI / ML proficiency: Ability to leverage AI tools to accelerate data analysis, apply basic machine-learning models when appropriate, and clearly interpret and communicate results while maintaining data quality and risk awareness
• Master’s degree in Applied Statistics, Mathematics, Actuarial Science, or a related field

Responsibilities

• Pull, prepare, and analyze large volumes of structured and unstructured safety data
• Support safety investigations through statistically sound analyses and exploratory data work
• Apply appropriate statistical methods to assess trends, risk, potential failure behavior, and anomalies
• Create clear, unbiased visualizations and summaries that accurately reflect the data
• Translate complex analytical findings into understandable insights for non-technical audiences
• Present results in written and visual formats to technical teams and leadership
• Collaborate with Safety, Engineering, Quality, and IT partners on cross-functional work
• Balance recurring sustaining analytics with ad-hoc data pulls and rapid-turn analyses
• Consult on data and analytics needs for safety investigations
• Perform statistical analyses using established methods and best practices
• Ensure analytical work is accurate, reproducible, and unbiased
• Build and maintain queries and datasets across multiple data sources
• Develop charts, dashboards, and visual summaries for ongoing monitoring and investigations
• Communicate assumptions, limitations, and results clearly and professionally
• Manage multiple concurrent requests in a fast-paced, ambiguous environment

Benefits

• From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees