• The primary responsibility of this role is to support Quality Promotion engineers to develop data models, tools, forecasting algorithms, prioritization & dashboards by using R/Python/Power BI to reduce warranty and to resolve quality issues quickly.
• Reporting to the Senior Engineering Manager - Quality Analytics and Innovation, the person in this role will support the Quality Promotion department's objective to innovate and develop quality analytics tools/process to improve development and field quality in efficient manner.

What you’ll be doing 

• Lead tool design including automated data ingest, data management, statistics/models (API), and visualizations.
• Developing data driven models to speed up early detection and early resolutions of quality issues. Develop tools (Python/R & Power BI) to quickly grasp the voice of customer and do diagnostic analysis
• Develop our next generation algorithms for forecasting and prediction of warranty and field issues by fusion of multiple data sources and more sophisticated data driving models. Develop models, tools and forecasting algorithms for connected car data and share to design groups in North America R&D (Research & Development)
• Close collaboration with Connected car and IT development team to ensure smooth integration of R&D (Research & Development) tools, templates & dashboards with other enterprise tools (Q360)
• Utilize and review multiple data sources (Field Reports, Warranty, Parts Sales, Recovered Parts, Customer Relations, etc.) to identify source of product quality issues, promote one voice and promote quick counter-measure activity by Design, Plant &/or Supplier 

• Experience building, implementing, and supporting medium to large scale solutions in Python and web/mobile applications.
• B.S. in Computer Science, related fields or commensurate work experience.
• Self-starter with the ability to work independently or as part of a project team with limited supervision.
• Experience using data analytics tools (VBA, R, Alteryx, PySpark, Python & Power BI)
• Experience in data-acquisition, data manipulation in cloud environments (Azure or AWS)
• Python Certification (foundational, associate, professional, or specialty).
• Web or mobile development experience. 
• Experience in data science, statistical modeling, data mining
• Experience in cloud computing infrastructure.