Product Safety Data Analytics Analyst

General Motors

United States

United States

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Über

About GM Join us at General Motors during this exciting time as we work towards our vision of Zero Crashes, Zero Emissions, and Zero Congestion. We are seeking passionate individuals to help create safer, smarter, and more sustainable mobility solutions. About Product Safety Data Analytics (PSDA) PSDA plays a crucial role in GM's safety ecosystem. Our mission is to enhance safety decision-making by identifying potential emerging vehicle safety issues through comprehensive analysis, mining, and monitoring of vast amounts of both structured and unstructured data. Our team collaborates across various areas, including customer complaints, engineering data, crash reports, vehicle telemetry, surveys, and research data to uncover trends, assess risks, and provide insights that drive informed decisions for safety, engineering, and leadership stakeholders. The Role The Product Safety Data Analyst will support Global Vehicle Safety and related organizations by conducting thorough, unbiased data analyses that guide safety investigations and decisions. This role emphasizes data extraction, preparation, analysis, visualization, and effective communication. You will work closely with safety engineers, statisticians, and analytics partners to ensure analyses are precise, timely, and presented clearly. What You'll Do (Responsibilities) Extract, prepare, and analyze large volumes of structured and unstructured safety data. Support safety investigations through rigorous statistical analyses and exploratory data studies. Utilize appropriate statistical methods to evaluate trends, assess risks, and identify anomalies. Create unbiased visualizations and summaries that accurately depict the data. Translate complex analytical outcomes into clear insights for non-technical audiences. Present findings in both written and visual formats to technical teams and leadership. Collaborate with cross-functional partners, including Safety, Engineering, Quality, and IT. Balance ongoing analytics tasks with rapid-response analyses and ad-hoc data requests. Consult on data and analytics needs arising from safety investigations. Conduct statistical analyses following best practices. Ensure all analytical work is accurate, reproducible, and impartial. Build and maintain queries and datasets from multiple data sources. Develop charts, dashboards, and visual summaries to monitor and investigate ongoing safety issues. Communicate assumptions, limitations, and results in a clear and professional manner. Manage multiple requests efficiently in a fast-paced and dynamic environment. Your Skills & Abilities (Required Qualifications) 3+ years of experience in analytics, statistics, or a related field after graduation. Bachelor's degree in Applied Statistics, Mathematics, Actuarial Science, or a related field. Strong understanding of statistical techniques, including: Time series analysis Categorical data analysis Multivariate analysis Logistic regression Linear and nonlinear modeling Outlier assessment / anomaly detection Proficiency in data visualization and chart creation. Experience in analyzing text or unstructured data through text mining and machine learning methods. Proficient in one or more programming or query languages (e.g., SQL, Python, R). Expertise in data preparation, cleaning, rationalization, and processing. Ability to independently manage a substantial workload. Comfortable working in an ambiguous environment and handling unplanned requests. Strong written and verbal communication skills. A demonstrated commitment to continuous learning. Tools & Technical Experience (one or more preferred) Data & Query: SQL; Databricks Programming: Python; PySpark (preferred) Analytics & BI: Power BI, Tableau; Excel What Can Give You a Competitive Edge (Preferred Qualifications) Experience with vehicle diagnostics, telemetry, or connected vehicle data. Familiarity with interpreting diagnostic signals, fault codes, and time-series vehicle data in an analytical or safety context. Understanding of vehicle safety systems, components, and field performance. Proficiency in AI/ML, with the ability to leverage AI tools for data analysis and apply basic machine-learning models while ensuring data quality and awareness of risks. A Master's degree in Applied Statistics, Mathematics, Actuarial Science, or a related field.

United States

Sprachkenntnisse

English

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