Manager, Operational Excellence Analytics

CVS Health•Island, KY

23h•$66,330 - $145,860•Hybrid

About The Position

The Manager of Operational Excellence Analytics is a key member of the Operational Excellence organization, responsible for owning the data architecture, advanced analytical models, and AI products that power decision-making across the CVS Distribution Center network. This role sits at the intersection of analytics engineering, advanced modeling, and applied AI — translating raw warehouse, labor management, and transportation data into productized datasets, semantic models, automation flows, and intelligent tools that operators, planners, and OpEx colleagues use every day to drive efficiency at scale. The role partners closely with IT’s Data Engineering and Data Science organizations while owning the OpEx-specific data architecture, automation, and AI development that drives operational improvement. The individual will also serve as a technical mentor to the broader OpEx organization — coaching colleagues across the network on data-driven problem solving and the proper use of data and AI tools. Role will be expected to travel ~20-30% of which 80% will be self-managed timing/location.

Requirements

Bachelor’s degree in Industrial Engineering, Computer Science, Data Science, or related engineering/science field, or an additional 4 years of experience in lieu of the WMS/LMS, SQL, and lean/CI requirements below.
3+ years experience in a manufacturing or distribution center environment.
2+ years experience with WMS and/or LMS systems and database structure, including data mapping and optimization of settings and configuration.
1+ years working directly with lean, process improvement, continuous improvement, or similar.

Nice To Haves

5+ years experience in a manufacturing or distribution center environment.
2+ years experience deploying production AI/ML or generative AI applications in a business or operational environment.
3+ years experience with semantic layer design and SQL — including data modeling, transformation logic, and performance optimization.
2+ years experience developing in PowerBI — including data modeling, DAX, and dashboard design at the network level.
Experience with analytics engineering tools and transformation frameworks.
Experience with workflow and process automation tools (Power Automate, Airflow, n8n, or similar).
2+ years working directly with lean, process improvement, continuous improvement, or similar.
Strong programming and scripting skills (Python, SQL, or similar) for automation, modeling, and data engineering work.
Strong interpersonal & communication skills, self-motivated, customer oriented, multi-tasking, and successful at managing multiple priorities and tasks.
2+ years of demonstrated success in managing projects.
APICS CPIM, CSCP, or CLTD Certified.
Six Sigma Green Belt Certified.
Experience working with a larger corporation and counterparts in other remote locations.

Responsibilities

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.
Develop and deploy advanced analytical models (forecasting, optimization, anomaly detection, classification) and AI/ML applications that solve operational problems across the DC network.
Build and maintain automation flows (Power Automate, Python, low-code tooling) that eliminate manual reporting, data preparation, and analysis effort across the OpEx organization.
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.
Partner with IT Data Engineering and Data Science teams on platform design, source system integrations, and shared infrastructure — ensuring OpEx requirements are well represented.
Use data, modeling, and AI to optimize WMS/LMS settings, configurations, and standards — driving measurable improvements in throughput, accuracy, labor utilization, and inventory accuracy.
Partner with routing, transportation, and inventory teams to identify and quantify business process optimization opportunities, including delivery scheduling, planning windows, and demand smoothing.
Translate analytical findings into specific, actionable recommendations for site and network leadership, including the financial business case for proposed change.
Support root cause analysis and corrective action efforts using statistical methods, modeling, and AI-assisted investigation in partnership with lean, IE, IC, and OpEx resources.
Train OpEx colleagues, site leadership, and cross-functional partners on OpEx developed tools and data-driven problem-solving methods.
Mentor OpEx colleagues on advanced analytical techniques and the proper interpretation of operational data.
Develop and maintain documentation, standard work, and learning paths that scale data literacy and AI fluency across the OpEx organization.
Serve as a technical advisor on cross-functional projects requiring advanced analytical or AI input.
Plan and execute multiple projects in parallel using strong project management discipline — managing risk, critical path, and dependencies to deliver on time.
Build the financial business case and project plan for proposed changes, then drive execution through to measurable, sustained results.
Communicate effectively across technical and non-technical audiences, balancing competing priorities across multiple teams and sites to achieve common goals.