AI Vendor Performance Scoring Developer

Orvix Works

Remote · $130k – $160k / year · Full-time · Posted 4 months ago

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About the role

We serve 340 retail clients who collectively manage relationships with 15,000 suppliers. Right now, vendor performance evaluation is a quarterly exercise based on spreadsheets and subjective ratings from category managers who favor vendors they like. We want to replace that with a continuous, objective scoring system that tracks delivery reliability, quality consistency, price competitiveness, and sustainability compliance. You'll design and build the vendor performance scoring engine: defining the composite metrics that capture what good vendor performance looks like across different product categories, building the data pipelines that aggregate signals from ERP systems, quality records, and logistics data, and creating the API that surfaces scores to procurement teams in real time. The hard part isn't the ML — it's getting the scoring logic right for industries as different as fresh produce and industrial components. This is a senior IC role with product ownership. You'll define the scoring methodology, socialize it with procurement domain experts, and have the final say on what gets shipped. Your counterpart is a senior product manager who handles client relationships.

Fully remote.

Responsibilities

Design composite vendor performance scoring methodology across product categories
Build data pipelines aggregating procurement, logistics, and quality signals
Develop APIs that surface vendor scores to procurement teams
Create calibration frameworks to ensure score consistency across categories
Build monitoring for scoring model drift and data pipeline health
Partner with procurement domain experts to validate and refine scoring logic

Requirements

6+ years in analytics or data science with procurement or supply chain domain experience
Strong Python and SQL skills with data modeling expertise
Experience designing scoring or rating systems with multi-dimensional inputs
Ability to translate business domain requirements into data models
Track record of shipping systems used by non-technical end users