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Safety Analytics Data Scientist - ENG0033763

Warren (Tech Ctr), Michigan, US

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Position summary

The Safety Analytics Data Scientist is responsible for identifying emerging vehicle safety issues by calculating and analyzing trends and patterns in customer complaint, engineering, crash, telematics, survey, and research data.  Must be analytical, adaptable, and detail oriented, producing high quality and accurate work product.  Also, most importantly, must enjoy and thrive at investigating and researching something that is difficult to find in a large defined space.
 
Responsibilities
  • Understand safety data and how to use it appropriately in data analysis
  • Apply best-in-class emerging issues methodologies for emerging issue identification
  • Perform analysis using industry leading text mining, data mining, and analytical tools
  • Develop innovative analytical approaches to root out, predict, and identify potential emerging issues through data analysis and reporting
  • Collaborate with Safety, Engineering, R&D, Quality and IT stakeholders to arrive at actionable insights
  • Manage safety cases, including pulling data and research, until handed off to subsequent stakeholders
  • Must be willing to read some verbatim comments to understand essence of potential safety issues
  • Present emerging issues analysis findings to internal audiences by synthesizing complex data and concepts into easy-to comprehend, comprehensive, and cohesive presentations
  • Support development of ontology and taxonomy for safety issues to ensure text mining is comprehensive
  • Provide feedback to solutions support team to provide and enhance best-in-class analysis tools
  • Participate in technical conferences, meetings, panels and other vehicle safety forums

The policy of General Motors is to extend opportunities to qualified applicants and employees on an equal basis regardless of an individual's age, race, color, sex, religion, national origin, disability, sexual orientation, gender identity/expression or veteran status. Additionally, General Motors is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us at Careers.Accommodations@GM.com. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Required skills:
  • 5+ years of work experience in Analytics or Business Intelligence
  • Understanding of vehicle safety technologies including design intent, function and intended performance in the field
  • Highly proficient with one or more data mining / predictive modeling tools such as SAS, JMP, Python, R, or Watson as well as proficient in SQL
  • Highly skilled at visual displays of quantitative and qualitative information and experience with visualization tools such as Tableau
  • Experience with statistical modeling, text mining, and/or machine learning
  • Strong understanding and experience with predictive / analytical modeling techniques, theories, principles, and practices
  • Ability to effectively communicate results and methodologies; must be comfortable presenting to executive leadership
  • Experience with data preparation, rationalization, and processing
  • Must be a self-starter
  • Willingness to learn new skills and methods as needed – continuous learning mindset
  • Must have strong drive for results
 
Preferred skills:
  • Master’s degree in Applied Statistics/Mathematics, Computer Science, Engineering, Operations Research or related field is highly preferred
  • Knowledge of GM IT systems and processes, especially in the areas of Engineering, Quality/Warranty, Customer Care and Aftersales, or OnStar
  • Five or more years of experience in vehicle development or validation of safety related systems or components
  • Working knowledge of safety standards and regulations
  • Experience with dealing with both structured and unstructured data
  • Multilingual competency is a plus

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