Data Scientist - Product Safety Data Analytics

generalmotors; Warren (MI); Hybrid; USD 110,000 - 160,000; Full time

Benefits offered by this job

Hybrid work model

Relocation benefits

Travel up to 25%

Job summary

General Motors is seeking a Data Scientist focused on hazard monitoring within the Product Safety Data Analytics team. You will develop analytics solutions to identify and monitor emerging vehicle safety issues, collaborating with business partners to understand challenges and automate workflows.

The role requires strong programming skills, experience with Python/SQL/Spark, Databricks, and data visualization tools, and a track record of delivering data-driven insights to senior leadership.

Qualifications

• 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 methods including outlier detection, time series, and multivariate analysis.
• Experience analyzing structured and/or unstructured data requiring data-mining techniques.
• Proficiency in Python and SQL/Spark with reusable, maintainable code.
• Knowledge of statistical graphics and visualization tools (Power BI, Tableau).
• Experience with Databricks, data pipelines, data preprocessing, and automation of recurring analytics.
• Ability to present results clearly to senior leadership and stakeholders.
• Understanding of vehicle safety technologies and their design intent.

Responsibilities

• Develop and standardize best practices for continuous monitoring of emerging safety issues for hazard monitoring.
• Strengthen data-analytics support for safety investigations with automated tools and process feedback.
• Analyze signals, patterns, and trends in large data sets to identify potential safety issues early.
• Support anomaly detection, diagnostics, prognostics, and root-cause analysis for safety topics.
• Design, build, and maintain repeatable analytics workflows using Python, SQL/Spark, Databricks, and related tools.
• Identify automation opportunities and implement data pipelines and reusable code.
• Prepare clear visualizations, summaries, and presentations for technical and non-technical audiences, including senior leadership.
• Communicate assumptions, methods, limitations, and findings clearly to support decision-making.
• Build knowledge of vehicle safety technologies and their field performance.

Skills

Python

SQL/Spark

Databricks

Statistical analysis

Data visualization

Communication

Problem solving

Vehicle safety knowledge

Education

Bachelor's degree in a quantitative field

Tools

Power BI

Tableau

Databricks

Spark

Job description

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 with hands‑on experience in statistical analysis, data interpretation, automation, and development of scalable analytical solutions. This role requires strong programming skills and the ability 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 data analyses, improve monitoring methods, and automate workflows.

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.
• Analyze signals, patterns, and trends in large and complex data sets to support early identification of 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 appropriate off‑the‑shelf technologies.
• Prepare clear visualizations, summaries, and presentations that synthesize complex data and concepts for technical and non‑technical audiences, including senior leadership.
• Communicate assumptions, methods, limitations, and findings clearly to support sound decision‑making.
• Build knowledge of vehicle safety technologies, their design intent and function, and their intended performance in the field.

Your Skills & Abilities (Required Qualifications):

• 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 methods such as 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 that require data‑mining techniques.
• Proficiency in Python and SQL/Spark, with the ability to develop clear, reusable, and maintainable analytical code.
• Knowledge of statistical graphics and experience with visualization tools such as Power BI and Tableau.
• 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):

• Experience 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, anomaly detection, or other advanced analytical techniques to support large‑scale safety data analysis.

#LI-KE2

GM does not provide immigration‑related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1‑B, OPT, STEM OPT, CPT, TN, J‑1, etc).This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.The selected candidate will be required to travel <25% for this role.Relocation benefits are available for candidates who qualify under company policy.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

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We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role‑related assessment(s) and/or a pre‑employment screening prior to beginning employment. To learn more, visit How we Hire.

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