Operational Excellence Analytics, Sr. Manager

Key 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.
• 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.
• Drive the OpEx analytics and AI roadmap — setting priorities and sequencing initiatives, while collaborating with OpEx and IT partners to execute initiatives on schedule.
• Through data, modeling, and AI, optimize WMS/LMS settings, configurations, and standards — driving measurable improvements in throughput, accuracy, labor utilization, and inventory accuracy.
• Lead cross-functional analysis 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.
• Lead root cause analysis and corrective action efforts using statistical methods, modeling, and AI-assisted investigation, partnering with lean, IE, IC, and OpEx resources.

Process Optimization Through Data Use

• Data use to optimize WMS/LMS settings, configurations, and standards.
• Identify and quantify business process optimization opportunities.
• Translate analytical findings into actionable recommendations.
• Lead root cause analysis and corrective action efforts.

Field Enablement & Mentorship

• 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 the technical lead and decision owner on cross-functional projects requiring advanced analytical or AI input.

Project & Change Management

• 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.

Required Qualifications

• Minimum of 5 years experience with semantic layer design and SQL — including data modeling, transformation logic, and performance optimization.
• 3+ years of demonstrated success managing projects, including cross-functional and network-level initiatives.
• 3+ years experience in a manufacturing or distribution center environment.
• 3+ years experience developing in PowerBI — including data modeling, DAX, and dashboard design at the network level.
• 3+ years experience with WMS (Manhattan Active a plus) and/or LMS systems and database structure, including data mapping and optimization of settings and configuration.
• 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.
• Travel up to 30%.

Preferred Qualifications

• 7+ years experience in a manufacturing or distribution center environment.
• 5+ years experience deploying production AI/ML or generative AI applications in a business or operational environment.
• Experience with analytics engineering tools and transformation frameworks.
• Experience with workflow and process automation tools (Power Automate, Airflow, n8n, or similar).
• 3+ years working directly with lean, process improvement, continuous improvement, or similar.
• 5+ years of demonstrated success managing projects, including network-level or cross-functional initiatives.
• APICS CPIM, CSCP, or CLTD Certified.
• Six Sigma Green Belt Certified.
• Experience working with a larger corporation and counterparts in other remote locations.
• Strong interpersonal & communication skills, self-motivated, customer oriented, multi-tasking, and successful at managing multiple priorities and tasks.