Sr. Manager, SC Analytics Optimization

Newell Brands•Atlanta, GA

About The Position

Newell Brands is a leading consumer products company with a portfolio of iconic brands like Graco®, Coleman®, Oster®, Rubbermaid®, Sharpie® and Yankee Candle® - and 24,000 talented teammates around the world. Our culture is built on values in action: Integrity, Teamwork, Passion for Winning, Ownership, and Leadership. We work together to win, grow, and make a real impact—supported by a high-performing, inclusive, and collaborative environment where you can be your best, every day. Job Summary: The Senior Manager, Supply Chain Analytics & Optimization leads a team of analysts, engineers, and data scientists responsible for supply chain network optimization, planning-focused business intelligence, and applied AI development. This role blends strategic thinking with hands-on technical leadership — owning enterprise-grade modeling capabilities, BI platforms that power planning decisions, and the build-out of AI solutions tailored to supply chain use cases.

Requirements

Bachelor's or Master's degree in Supply Chain, Data Science, Engineering, Business Analytics, or a related field
7+ years of progressive experience in supply chain analytics, network optimization, or data science, with at least 2 years in a people management role
Demonstrated ability to lead complex, cross-functional analytical projects from design through delivery
Strong hands-on proficiency in Python, SQL, and PySpark for data manipulation, modeling, and pipeline development
Experience with Databricks and Azure cloud services for scalable data and ML workflows
Proven track record translating analytical outputs into executive-level business recommendations
Strong communication and stakeholder management skills across technical and non-technical audiences

Nice To Haves

Experience with supply chain network design tools (e.g., Coupa SCGX / Llamasoft, Optilogic Cosmic Frog)
Familiarity with Power BI, including DAX and enterprise data model design
Exposure to AI/ML deployment patterns, MLOps, or LLM-powered application development
Experience working within a hub-and-spoke or center-of-excellence operating model
Knowledge of integrated business planning (IBP) or S&OP processes
Background in consumer goods, retail, or manufacturing supply chain environments

Responsibilities

Lead and develop a multi-disciplinary team spanning supply chain optimization, BI analytics, and applied AI
Set team priorities, manage capacity, and ensure high-quality delivery across concurrent workstreams
Provide technical mentorship, career pathing, and performance development for analysts, engineers, and data scientists
Foster a culture of rigor, curiosity, and continuous improvement
Own enterprise supply chain network modeling — DC network design, transportation optimization, inventory positioning, and scenario-based cost/service tradeoff analysis
Translate complex network modeling outputs into executive-ready recommendations with clear business cases
Partner with Supply Chain leadership to support major capital and operational decisions with data-driven scenario analysis
Maintain and evolve optimization tooling and analytical frameworks using Coupa SCGX, Python, and cloud-native compute
Oversee the design and delivery of supply chain BI solutions that enable data-driven decision-making across planning, operations, and leadership
Drive development of dashboards, scorecards, and self-service reporting capabilities using Power BI and Databricks
Ensure data pipelines powering supply chain analytics are reliable, governed, and scalable on Azure
Partner with cross-functional stakeholders to translate business questions into analytics products that drive action
Lead development and deployment of AI capabilities targeted at supply chain and planning use cases — including demand signal processing, automated insights generation, planning workflow automation, and intelligent decision support
Partner with planning teams to identify and prioritize high-value AI opportunities across S&OP, IBP, and operational planning processes
Collaborate with the broader Quantum Leap AI Engineering team to align on standards, platforms, and reusable components
Evaluate and pilot emerging AI tools and techniques relevant to network design, planning, and supply chain operations
Ensure AI solutions are production-grade, governed, and aligned with enterprise AI standards on Azure and Databricks