Responsibilities

• Develop robust reporting and insights while enabling the ability for self-service reporting of key business performance metrics
• Use agile development principles to produce continuous value while readily adapting to change
• Co-own the ongoing development of the CPOD Spares & Warranty Pulse as the intelligent cockpit for the Spares & Warranty business
• Own the ETL approach and execution for acquiring data from multiple and disparate sources
• Leverage a deep understanding of supply chain fundamentals to proactively collect data, analyze, and provide insights that drive improved service parts business performance
• Leverage a pattern-based approach to analyze and discover hidden patterns in the data that unlock new insights that optimize business performance
• Manage and maintain a SQL-on-Azure instance to support aggregation of data and 100+ reports
• Participate in a bi-weekly scrum process to deliver prioritized and ad-hoc features specific to reporting and analysis
• Build strong working relationships across multiple internal disciplines and teams
• Leverage deep expertise with SQL and PowerBI and other relevant tools & technologies to perform rapid ad-hoc insights requests for CVP-level audiences
• Engineer, execute, and then refine process and tool models to improve operational efficiency and enable scale for service parts operations by providing rich insights that enable prompt and measurable improvement to key performance indicators
• Design, develop, and document architectural solutions and processes
• Develop next generation of analytics and statistical models to enable a 10x growth in throughput while reducing cycle time and variation.
• Design, develop, and maintain data pipelines, back-end, and front-end services for reporting, monitoring, analysis, and related functions
  
  

Qualifications

Required Qualifications:

•  and Statistics or 4+ years of equivalent work experience.
• 5+ years combined experience into Data Science, Program Management, Software Development, technical/engineering role(s) including demonstrated expertise in R/Python, PowerBI, or SQL, or equivalent technologies.
• Experience working on Data Engineering workload.
  
  

Preferred Qualifications

• Experience with supply chain analytics and modeling techniques
• Experience with big data technologies such as Azure Data Lake, Databricks, Hive, Spark, or Scope - Data science knowledge and experience with Azure Machine Learning
• Experience developing and deploying ML models to solve real-world problems.
• Experience with SAP ECC, OER, and IBP modules is desirable.
• Experience in High-tech Supply Chain, Reverse Logistics, or Service Parts industry is a plus.