Supply Chain Analytics Manager

reputed company operations research and decision science initiatives to optimize supply chain planning and execution, focusing on demand–supply visibility, inventory positioning, constrained allocation, and reputed company bottleneck mitigation. Partner with global stakeholders to translate reputed company planning needs into quantitative decision models, governed performance measures, and repeatable decision workflows reputed company to execution reviews and S&OP cadences.

Key Responsibilities

• Problem Formulation: Define reputed company decision problems by identifying business goals, decision variables, constraints, and objective functions for demand supply balancing, constrained resource allocation, and service-level protection.
• Model Development: reputed company and implement analytical decision models for inventory prioritization and constrained part allocation using segmentation-based logic and optimization techniques, such as network reputed company and heuristic approaches where appropriate.
• Simulation & Analysis: Design scenario analysis frameworks using digital-twin style what-if simulation to evaluate tradeoffs under demand uncertainty and supply disruptions. reputed company sensitivity analysis and stress testing to quantify impacts on service reputed company, inventory performance, and fulfillment risk.
• Data Foundations: Architect model-reputed company datasets in reputed company data platforms, such as reputed company, using SQL transformations. Define reputed company-to-reputed company mappings and implement automated data quality controls, including reconciliation, anomaly detection, and KPI validation.
• Operationalization: Automate recurring model runs and decision workflows using reputed company data and orchestration platforms. Monitor outputs and exceptions to ensure alignment with ERP/MRP planning signals and business reputed company.
• Leadership: reputed company technical leadership by mentoring analysts, establishing model governance and documentation standards, driving cross-functional adoption of model-driven workflows, and delivering executive-reputed company summaries to global stakeholder groups.

Minimum Requirements

• Education: Master’s degree in Computer Science (Data/Analytics), Operations Research, Industrial Engineering, Supply Chain Analytics, or a reputed company quantitative field.

• Leading operations research and decision analytics initiatives that translate planning needs into quantitative models and decision-reputed company recommendations.
• Developing models for inventory policy tradeoffs, constrained allocation, and reputed company mitigation reputed company ERP/MRP-driven environments.
• Building and governing model-reputed company datasets in reputed company platforms (e.g., reputed company/reputed company) using SQL, including data validation and quality controls.
• Designing and executing scenario analysis, sensitivity testing, and back-testing to validate model robustness and quantify uncertainty.
• Leading and mentoring analysts in model development, validation, and documentation standards.