September 15, 2021

  • Bachelor’s level degree in Business, Supply Chain, Procurement, Finance, Accounting, Analytics, Mathematics, Economics, and/or related discipline
  • 3+ years of experience in quantitative or process improvement roles, using data analytics, mining, and/or visualization to solve problems
  • 1+ years of experience in project management roles, with experience in scoping, leading, and delivering projects
  • Proficiency in Excel (e.g. conditional formatting, PivotsTables, lookups, etc.) and experience performing ad hoc analysis
  • Working knowledge of business intelligence reporting tools (e.g. Cognos, Tableau, MicroStrategy, QuickSight, systems using SQL-based queries, etc.
The North American (NA) HR Regional Center (HRRC) Data Analyst (DA) converts people, process, and technology data into meaningful, actionable insights for the Amazon NA HRRC. The NA HRRC DA is skilled in process improvement, project management, and data analysis, and they leverage a variety of People eXperience and Technology (PXT) data platforms, processes, policies, and tools to develop solutions supporting PXT performance. The role requires understanding customer needs, building and implementing dashboards, defining measurement mechanisms & success measures, and reporting business performance on a regular basis.
The successful candidate should be a detail-oriented, organized planner with the demonstrated ability to respond effectively and efficiently. The candidate should be self-driven and possess the ability to work in an ambiguous environment with minimal guidance or supervision. As such, the candidate must be skilled at anticipating problems, constructing the solution, and managing multiple priorities. The candidate should effectively use HR data to provide meaningful insights and recommendations to HR operational leaders, create any subsequent project proposals, and track any deliverables.
  • Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards to drive key business decisions
  • Establish scalable, efficient, automated processes for data analyses
  • Display complex quantitative data in a simple, intuitive format, and present findings in a clear and concise manner
  • Synthesize data to provide impactful insights and process improvement recommendations
  • Partner closely with the HR teams to understand team barriers
  • Measure the effectiveness Associate (AA) engagement processes in HRRC
  • Identify areas where no standard work exists and develop proposals to implement in HRRC
  • Use people data to identify trailing indicators, research root causes, validate assumptions, and create related action plans for HRRC and Lines of Business (LOB) supported.
  • Analyze HRRC trends in attendance, attrition, overtime, or Engage@Amazon, and provide insights/suggestions for AA program improvements
Partner with HRRC Site Leaders to analyze organizational health data across sites in the region, and provide insights/suggestions to drive improvements in organizational health categories (including 1:1s, Engage@, Connections, escalations, succession planning, etc.)
  • Master’s degree
  • Experience aggregating disparate data spanning multiple sources and reporting tools
  • Working knowledge of continuous improvement methodologies such as Lean Six-Sigma, DMAIC/Agile, or root-cause analysis approaches
  • Strong written and verbal communication
  • History of developing and implementing new ideas and creative solutions for improved efficiency and effectiveness in an ambiguous, fast-paced environment.
  • Experience participating in cross-functional, multi-geographic teams to define trends, measure the effectiveness of programs, and develop/implement new solutions
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https: