Procurement Data & Planning Analyst

• Consolidate daily supplier price blasts (SMS/Viber/email) into the Purchasing Master File
  
• Track prices against the Valenzuela market benchmark and flag outliers before any buy decision
  
• Run the three-scenario price model on every significant purchase: lowest market price vs. last
  selling price vs. last purchase price — always anchoring to whichever is most favorable
  

• Maintain the demand-to-import gap tracker across all three categories (beef, chicken, pork)
  
• Monitor import arrival timelines against the 98-day procurement lag and flag upcoming supply
  gaps early
  
• Support SPS permit pre-checking and track outstanding permit status with the Category Specialist• Keep the import procurement decision model current and flag data quality issues proactively
  

• Track warehouse inventory aging weekly; flag SKUs approaching slow-mover thresholds
  
• Prepare the commodity price list for trader liquidation of aged stock, with recommended price
  bands
  
• Surface cash flow risk from stagnant import inventory before it becomes an operational problem
  

• Compile and clean all procurement data inputs for the monthly S&OP meeting
  
• Produce a one-page data summary showing planned vs. actual imports, coverage gaps, and key
  price variances
  
• Maintain a running log of S&OP decisions and follow-up action items
  

• Build and maintain a simple supplier scorecard tracking: fill rate, price variance vs. quoted, lead
  time adherence, and payment terms compliance
  
• Flag supplier performance trends to the Category Specialist for negotiation use
  
• Support the groundwork for formal supplier audits as Rare's buying volume grows
  

Requirements

• Bachelor's degree in Business Administration, Supply Chain Management, Economics, Statistics, or a related field
  
• Strong Microsoft Excel proficiency: pivot tables, VLOOKUP/XLOOKUP, basic financial modeling
  
• Exposure to supply chain, food trading, commodity sourcing, or a similar field
  
• Ability to distill raw data into a clear, decision-ready summary for non-technical stakeholders
  
• Organized and process-driven — you own a workflow end-to-end and maintain it consistently
  
• Analytical mindset: you spot anomalies in a dataset without being asked, and you follow the number until you understand it​