Operational Excellence Analytics, Sr. Manager

CVS Health CVS Health · Healthcare · Work at Home, RI +53 · Corporate

This role is responsible for driving data architecture strategy, advanced analytical models, and AI products within the CVS Distribution Center network. It sits at the intersection of analytics engineering, advanced modeling, and applied AI, translating data into productized datasets, semantic models, automation flows, and intelligent tools to improve operational efficiency. The role involves designing and maintaining a semantic data layer, developing and deploying AI/ML applications, building automation flows, and creating PowerBI dashboards. It also requires owning platform requirements, driving the analytics and AI roadmap, and optimizing processes using data, modeling, and AI. The role includes field enablement, mentorship, and project management, with a focus on solving operational problems and driving measurable improvements.

What you'd actually do

  1. Design and maintain the OpEx semantic data layer in Snowflake — building productized datasets that serve as the trusted source for OpEx reporting, modeling, and AI applications across the network.
  2. Develop and deploy advanced analytical models (forecasting, optimization, anomaly detection, classification) and AI/ML applications that solve operational problems across the DC network.
  3. Build and maintain automation flows (Power Automate, Python, low-code tooling) that eliminate manual reporting, data preparation, and analysis effort across the OpEx organization.
  4. Develop network-level PowerBI dashboards on top of the semantic layer to support daily management, performance management, and process improvement at both site and network levels.
  5. Own OpEx's platform requirements and represent them directly in platform design, source system integration, and shared infrastructure decisions made jointly with IT, Data Engineering and Data Science teams.

Skills

Required

  • semantic layer design
  • SQL
  • data modeling
  • transformation logic
  • performance optimization
  • project management
  • manufacturing or distribution center environment experience
  • PowerBI development
  • DAX
  • dashboard design
  • WMS/LMS systems
  • database structure
  • data mapping
  • optimization of settings and configuration
  • lean, process improvement, continuous improvement experience
  • Python
  • automation
  • modeling
  • data engineering

Nice to have

  • Manhattan Active WMS
  • analytics engineering tools
  • transformation frameworks
  • workflow and process automation tools (Power Automate, Airflow, n8n, or similar)
  • generative AI applications

What the JD emphasized

  • 5 years experience with semantic layer design and SQL
  • 3+ years of demonstrated success managing projects
  • 3+ years experience in a manufacturing or distribution center environment
  • 3+ years experience developing in PowerBI
  • 3+ years experience with WMS (Manhattan Active a plus) and/or LMS systems
  • 2+ years working directly with lean, process improvement, continuous improvement, or similar
  • Programming and scripting experience with (Python, SQL, or similar) for automation, modeling, and data engineering work
  • 5+ years experience deploying production AI/ML or generative AI applications in a business or operational environment

Other signals

  • Develop and deploy advanced analytical models (forecasting, optimization, anomaly detection, classification) and AI/ML applications that solve operational problems across the DC network.
  • Drive the OpEx analytics and AI roadmap — setting priorities and sequencing initiatives, while collaborating with OpEx and IT partners to execute initiatives on schedule
  • Use data, modeling, and AI to optimize WMS/LMS settings, configurations, and standards — driving measurable improvements in throughput, accuracy, labor utilization, and inventory accuracy.
  • Lead root cause analysis and corrective action efforts using statistical methods, modeling, and AI-assisted investigation, partnering with lean, IE, IC, and OpEx resources.