Hybrid
Warren, Michigan, United States of America
Full time
JR-202620524
Job Description
The Role
The Product Safety Data Analytics team is seeking highly motivated and qualified candidates for the position of Data Scientist focused on hazard monitoring.
This is a great opportunity for an innovative data scientist/statistician with strong hands-on experience in statistical analysis, data interpretation, automation, and development of scalable analytical solutions. This role requires strong programming skills and deep knowledge of statistical techniques to solve complex problems, automate analytical workflows, support safety investigations, and strengthen hazard monitoring capabilities. You will be part of a highly collaborative team that values growth, creativity, and a relentless focus on data-driven business transformation.
In this role, you will develop and improve analytical solutions to identify, monitor, and analyze potential emerging vehicle safety issues. You will work closely with business partners to understand their challenges and needs, perform appropriate statistical analyses, improve monitoring methods, automate workflows, and provide technical guidance and mentorship across the team.
What You'll Do (Responsibilities):
Develop and help standardize best practices for continuous monitoring of emerging safety issues for use in safety hazard monitoring
Strengthen data-analytics support for safety investigations through improved methods, automated tools, and feedback loops for process improvement
Perform appropriate statistical analyses to deliver sound, unbiased, and actionable results
Analyze signals, patterns, and trends in large and complex data sets to support early identification of potential safety issues
Apply methods such as time series analysis, categorical data analysis, sampling, and multivariate analysis to support investigations and decision-making
Support anomaly detection, diagnostics, prognostics, and root cause analysis for safety-related topics
Identify, design, and implement automation opportunities using a combination of custom software development and off-the-shelf solutions
Develop scalable automated analytical tools, data workflows, and monitoring approaches that improve execution efficiency and consistency
Communicate findings clearly and tell a concise, data-driven story to a wide range of stakeholders, from analyst to senior leadership
Apply strong business acumen and technical judgment to expand and strengthen hazard-monitoring analytics support
Work independently on complex assignments while collaborating effectively across functions
Serve as a resource and mentor for less experienced team members
Your Skills & Abilities (Required Qualifications):
B.S. in a quantitative discipline such as Statistics, Mathematics, Econometrics, Operations Research, or another relevant degree
5+ years of work experience in applied statistics, analytics, engineering, data science, or a related field
Strong background in statistical data analysis such as time series, categorical data analysis, multivariate analysis, and sampling design
Strong background in anomaly detection, diagnostics and prognostics, and root cause analysis
Demonstrated experience in large-scale data analytics
Strong programming capability in Python, SQL, and related analytical tools
Experience working with modern data environments such as 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
What Will Give You a Competitive Edge (Preferred Qualifications):
M.S. in a quantitative discipline such as Statistics, Mathematics, Econometrics, Operations Research, or another relevant degreeExperience in vehicle development or validation of safety-related systems or components
Experience supporting safety investigations or field-performance analytics
Experience working within GM's data ecosystem
Experience using GM's cloud technology stack for data science and analytics
Experience applying natural language processing or other advanced analytical techniques to support large-scale safety data analysis
LI-KE2
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