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Under general supervision of the Supply Chain Modeling & Optimization Director, the Supply Chain Network Modeler is responsible for developing, maintaining, and applying network models that transform complex supply chain data into actionable insights to support strategic and operational decision making.
This role works collaboratively with cross functional stakeholders and remote teams to identify modeling use cases, translate business questions into quantitative network scenarios, and evaluate tradeoffs across cost, service, capacity, risk, and growth. The Network Modeler documents assumptions, validates data inputs, and communicates findings through interactive dashboards, visualizations, and structured storytelling to enable informed decisions.
Primary Duties and Responsibilities
Develop, maintain, and enhance end-to-end supply chain network models covering facilities, flows, transportation, capacity, inventory, and service performance.
Translate business problems into scenario-based network analyses that evaluate cost to serve, service levels, capacity constraints, and investment alternatives.
Partner with Supply Chain, Transportation, Finance, Engineering, and Operations teams to:
Scope modeling opportunities
Gather and validate inputs
Align scenarios and assumptions
Interpret and communicate results
Support network optimization and simulation initiatives by building scalable models and reusable templates for recurring analyses.
Create standardized dashboards and visualizations to communicate model inputs, outputs, and trade‑offs to technical and non‑technical audiences.
Document modeling assumptions, methodologies, data sources, and limitations to ensure transparency, repeatability, and governance.
Maintain and improve data models and datasets that support supply chain network analytics.
Contribute to the development of modeling best practices, templates, and training materials to support the growth of internal “citizen modelers.”
Stay current with emerging trends in network modeling, optimization, simulation, and advanced analytics.
Experience and Educational Requirements
Bachelor’s or Master’s degree in Industrial Engineering, Operations Research, Supply Chain, Data Analytics, Mathematics, Statistics, Computer Science, or a related field.
Typically requires 3+ years of experience in supply chain analytics, network modeling, optimization, or related quantitative roles.
Demonstrated experience applying analytical techniques to business problems and translating results into actionable recommendations.
Supply chain industry or distribution network experience strongly preferred.
Technical Skills and Qualifications
Solid foundation in quantitative modeling, statistics, and optimization techniques.
Hands‑on experience with supply chain network modeling or optimization tools (e.g., Llamasoft/Coupa, AnyLogistix, OptiLogic, or similar) preferred.
Proficiency in data analysis and modeling languages such as Python, R, SQL, SAS, Databricks.
Experience working with large datasets and integrating data from ERP, WMS, TMS, transportation, inventory, or forecasting systems.
Familiarity with business intelligence and visualization tools (Power BI, DataBricks, Tableau, Qlik, etc.).
Understanding of cost to serve, transportation tradeoffs, capacity planning, and service optimization concepts.
Experience building business cases and proposals that need to be presented in front of the leadership team for decision making. Understanding of trade offs between capex and opex.
Lean, Six Sigma, or continuous improvement experience is a plus.
Minimum Skills, Knowledge, and Abilities
Team oriented and highly collaborative working style.
Strong analytical, conceptual, and problem solving skills.
Ability to communicate effectively—both verbally and in writing—with technical and non‑technical stakeholders.
Strong presentation and storytelling skills, with the ability to explain complex modeling outcomes clearly and persuasively.
Strong organizational skills and attention to detail.
Ability to manage multiple tasks and prioritize effectively in a dynamic environment.
Demonstrates sound judgment and discretion when working with sensitive or complex information.
Comfortable working in a remote, cross functional, multidisciplinary environment.
Growth mindset with a strong interest in solving business challenges and continuously improving modeling capabilities.
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EXPERIENCE AND EDUCATIONAL REQUIREMENTS:
· Bachelor or Master’s degree in data analytics, mathematics, statistics or computer science or related field.
· Typically requires 3 or more years of relevant quantitative and qualitative and analytics experience.
· Solid knowledge of statistical techniques.
· The ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.
· Strong programming skills (such as Hadoop MapReduce, Spark or other big data frameworks, Java, Python) and statistical modeling (like SAS or R).
· Experience using machine learning algorithms.
· High proficiency in the use of statistical packages.
· Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.
· Lean or Six Sigma experience improving processes by using data insights
· Strong communication and interpersonal skills.
· Supply Chain industry/business knowledge preferable.
MINIMUM SKILLS, KNOWLEDGE AND ABILITY REQUIREMENTS:
Building Relationships – Works collaboratively with others
Business Function Knowledge – Open minded; Proposes solutions to complex problems
MINIMUM SKILLS, KNOWLEDGE AND ABILITY REQUIREMENTS:
Benefit offerings outside the US may vary by country and will be aligned to local market practice. The eligibility and effective date may differ for some benefits and for team members covered under collective bargaining agreements.
Cencora is committed to providing equal employment opportunity without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status or membership in any other class protected by federal, state or local law.
The company’s continued success depends on the full and effective utilization of qualified individuals. Therefore, harassment is prohibited and all matters related to recruiting, training, compensation, benefits, promotions and transfers comply with equal opportunity principles and are non-discriminatory.
Cencora is committed to providing reasonable accommodations to individuals with disabilities during the employment process which are consistent with legal requirements. If you wish to request an accommodation while seeking employment, please call 888.692.2272 or email hrsc@cencora.com. We will make accommodation determinations on a request-by-request basis. Messages and emails regarding anything other than accommodations requests will not be returned
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