Supply Chain Business Analytics Manager

Pharmavite•Santa Clarita, CA

6d•$100,000 - $166,000•Onsite

About The Position

The Supply Chain Business Analytics Manager defines and executes the analytics strategy for Customer Service, Supply Chain Planning, and Integrated Logistics. This role leads analytics professionals and partners with business leaders and IT to develop scalable data models, governance standards, automated reporting, and advanced analytics capabilities that improve visibility and decision-making across the end-to-end supply chain. The manager drives adoption of predictive, prescriptive, and AI-enabled analytics to improve forecast accuracy, inventory optimization, service levels, logistics cost performance, and overall supply chain efficiency while ensuring data integrity, accessibility, and responsible AI use.

Requirements

Bachelor’s degree in business, Supply Chain, Operations Management, Analytics, or a related field, or equivalent professional experience.
5-10+ years of progressive experience in Data Analytics or Business Intelligence with at least 3 years of experience defining and executing a multi-year Data Strategy or Roadmap, and/or Center of Excellence.
Expert proficiency in SQL for complex querying and hands-on mastery of at least one major BI platform (e.g., Tableau, Power BI).
Demonstrated working knowledge of data modeling concepts, cloud data architectures (ETL/Data Warehouse), and statistical methodologies sufficient to scope and govern advanced analytics projects.
Functional understanding of analytical scripting languages (Python or R) for advanced analytics and statistical modeling.
Proven ability to extract, transform, and analyze data from ERP systems.
Strong communicator with experience leading cross-functional meetings and influencing stakeholders in a matrixed environment.
Skilled in prioritization, strategic thinking, and driving continuous improvement.
Demonstrated experience automating and integrating data across multiple platforms and systems.
Advanced expertise in data visualization and analytics tools (Power BI, Tableau, Alteryx).
Experience leading cross-functional meetings and influencing stakeholders in a matrixed environment.
Strong project management skills managing complex, interdependent initiatives.
Excellent communication and collaboration skills, with the ability to translate technical concepts into business insights.
Strong business acumen with a balance of analytical rigor and pragmatic execution.
Expert-level capability in establishing foundational data management and governance practices.
Self-starter with a strong bias for action and a passion for innovation.

Nice To Haves

Master’s degree (MBA, Predictive Analytics, Data Science, or Information Systems) preferred.
Experience with JD Edwards, Hyperion, Oracle, and Microsoft automation tools preferred.

Responsibilities

Lead & Build Capability: Foster a culture of data-driven decision-making and continuous improvement across the Supply Chain organization.
Drive adoption of advanced analytics and AI-enabled tools by embedding insights into operating rhythms, training users, and measuring usage and business impact.
Lead and develop analytics professionals with clear priorities, standards, and career paths.
Drive Business Insights & Reporting: Support development and execute a reporting and analytics roadmap aligned to supply chain and operational business objectives including shifting the organization from descriptive reporting to predictive and prescriptive decision support.
Design AI-enabled dashboards, KPIs, and decision tools used in weekly, monthly, and S&OE rhythms.
Translate demand, supply, inventory, and capacity signals into actionable planning insights that support S&OE and business decision-making.
Partner with Customer Service, Planning and Logistics leaders to identify and deliver high-value analytics use cases related to service, cost, inventory and operational performance.
Priority projects include: Forecast accuracy & bias, Inventory optimization & service trade-offs, Capacity and constraint planning, Disruption and risk sensing.
Define success metrics and track business impact of analytics solutions, including improvements in service, forecast accuracy, inventory health, cost, productivity, and decision speed.
Develop analytics that improve visibility to freight, warehousing, distribution, and cost-to-serve performance.
Identify logistics cost drivers and opportunities to improve network, transportation, and service trade-offs.
Build Scalable, Governed Solutions: Define business requirements for data models, data pipelines, semantic layers, and reporting structures that support scalable analytics across Customer Service, Planning, and Logistics.
Ensure solutions are automated, reusable, and scalable — not one-off analyses.
Define data governance, validation, and model monitoring to ensure trust and responsible AI use.
Partner with IT on Data Foundations: Collaborate with IT and business teams to translate reporting requirements into scalable business solutions.
Support system enhancements and process improvements related to reporting and analytics.
Facilitate cross-functional alignment through clear communication of business insights and operational performance.