The project will focus on integrating suppliers, subtier, forecast, and capacity data into a centralized Power BI dashboard, enhanced with AI/ML predictive models to identify potential delivery gaps before they impact production.
The solution will analyze demand trends, supplier capacity constraints, geographical dependencies, and sourcing concentration to provide early-warning indicators and actionable insights for Supplier Account Management team.
The objective is to have zero last-minute surprises caused by subtier shortages and improve proactive risk mitigation through better forecasting and scenario analysis.
Desired Skills Required
Business Analytics /Supply Chain Analytics (Preferred)
Power BI dashboard development and data modeling
Python, SQL, or data engineering fundamentals
Machine Learning / Predictive Analytics
Data visualization and storytelling
Strong problem-solving and stakeholder communication skills
Learning Outcome
Apply business analytics techniques to solve real-world supply chain challenges.
Build end-to-end Power BI solutions using multiple data sources.
Develop predictive models for forecasting supply chain risks and capacity constraints.
Understand multi-tier supply chain structures, supplier risk management, and resilience strategies.
Generate actionable insights that support proactive decision-making and risk mitigation.
Gain practical experience in AI-enabled supply chain planning and digital transformation initiatives.
Additional Information
Time Type
Full time
Employee Type
Intern / Student
Travel
No
Relocation Eligible
Yes
Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.
