General Motors Data Scientist/Statistician – Manager Level - GLO0002291 in Detroit, Michigan

The Global Product Planning Advanced Analytics teamproactively leverages data and tools to drive decisionmaking in the GPP organization by coordinating existing and new analyticsprojects across GPP. The Data Scientist will execute small to midsize focusedad hoc projects and manage larger engagements within the GM Analyticsorganization.

  • Merge pockets of existing analyticswithin GPP and link to broader analytics community
  • Collaborate with IT Advanced Analyticsfor major analytics projects and leverage additional capabilities to helpmanage GPP effort
  • Perform peer reviews on analyticsdeliverables
  • Provide technical training, asneeded, to Advanced Analytics staff
  • Develop appropriate analyticsmethods
  • Collaborate with business teams toenable integration of tools and analysis into business decision making process
  • Manage stakeholder needs across the organization andinfluence without formal authority

Knowledge:

  • Long-Term Forecasting, Planning, and Market Researchprocesses
  • GVDP deliverables
  • Planning (GM3PD), Forecasting(GFS), and Volume databases(GSRA)
  • GM vehicle and powertrain portfolio
  • Competitive Intelligence
  • Automotive industry knowledge, including policies,competitor activities, and industry trends
  • Forecasting related data – third party forecast houses,historical data sources, research data sources

  • Setting priorities and alignment of project prioritieswith business strategy

  • Managing complex projects
  • Leading small direct and cross-functional teams
  • Proposing solutions and strategiesto business challenges that drive business impact
  • Breaking down complex problems and projects intomanageable goals
  • Influencing people, skilled in communicating the benefitsof data analysis to business line professionals to create a value proposition
  • Building trust, respect and cooperation among teams
  • Building predictive models andmachine-learning algorithms
  • Analyzing large amounts ofinformation to discover trends and patterns
  • Monitoring and sustaining modeleffectiveness
  • Presenting complex information usingdata visualization techniques

Required Technical Background:

  • 4 Year College Degree/Master'sdegree preferred in Economics, Mathematics, Statistics, Computer Science,Operations Research, Engineering, or other quantitative field with emphasis on statisticalanalysis, econometric modeling and/or forecasting
  • Proficient in one or more coreanalytical tools/suites/languages such as SAS, Python, R, Spark Scala andunderstand their limitations
  • Proficient in one or more analyticalmethodologies such as numerical optimization, econometric modeling andforecasting, and machine learning

Preferred:

  • Preferred – 5-9+ years’ experience creating data products
  • Quantitative Master’s degree preferred