Operations Expert with Python for AI Supply Chain Task Design

Anywhere in the World • On-site • Senior • 2 days ago
Data Analyst
Auf einen Blick

Task-basierte Aufgabe zum Entwerfen von Supply-Chain-Benchmarks für KI-Agent-Evaluation mit Python-Automatisierung.

💰 ~$5.000–12.000/h (geschätzt) 📊 Mid-Level 🕒 Contract 🌍 Remote 🗺️ Worldwide
  • 3+ Jahre Supply Chain Erfahrung
  • ERP/WMS-Systeme
  • Python-Kenntnisse
  • Prozessdokumentation
Python

Gehalt geschätzt anhand Task-basierte Kompensation, ~60-75 Minuten pro Task, Supply Chain Expert. Kein Gehalt in der Anzeige angegeben.

✅ Geeignet für
  • Supply Chain-Spezialistinnen
  • Operations-Fachleute
  • Python-versierte Data Professionals
🚫 Weniger geeignet
  • Junior-Level Kandidaten
  • Reine Development-Positionen
💡 Gut zu wissen
  • Task-basierte Bezahlung pro 60-75 Minuten
  • Anti-Spam-Anforderung im Original - ignorieren
  • Verfügbarkeit ab 4. November 2026 erforderlich

Overview

A fast-growing AI data company is hiring supply chain practitioners to design expert-level Terminal-Bench tasks for evaluating AI agents. You will turn real planning work into end-to-end challenges, each with files, a working solution and an automated correctness check. The goal is to build a benchmark grounded in real operations work.

***THIS IS A TASK BASED COMPENSATION MODEL. PLEASE CHECK THE APPLICATION QUESTIONS FOR MORE DETAILS.***

Responsibilities

• Design expert-level Terminal-Bench tasks by turning a real supply chain task from your work into a challenge an AI agent solves end to end.

• Define the files, data exports and systems each task runs on, such as ERP, MES and WMS extracts, so the scenario reflects realistic planning conditions.

• Write a working solution for each task, for example a 5-day production plan, and confirm it can be solved in 60 to 75 minutes.

• Build the automated check that proves the result is correct, using tests or scripts that accept valid answers and catch planning errors objectively.

• Document the written rules, constraints and SOPs that decide each case, along with realistic edge cases, data inconsistencies and common planner errors from your process.

• Iterate on tasks based on reviewer feedback, keeping instructions unambiguous, data consistent and the solution and verification reproducible in a command-line environment.

Skills/Experience

• 3+ years of hands-on supply chain or production planning work (not only studying, selling or managing it), or a PhD with active research in the subfield

• Did the work within the last 3 years and can name the systems, tools, data and rules used

• Personally executed a process where each case is decided by written rules such as SOPs, planning rules or constraints

• Worked inside systems of record (ERP, WMS) and with their exports or reports

• Can describe edge cases, data inconsistencies and common planner errors, and how a mistake would be caught

• Technical fluency in Python or another language and the command line, plus files, CSV/JSON, APIs or databases

• Available to start around November 4, 2026

Nice-to-have

• Automated or audited the process with scripts, SQL, RPA or rules engines

• 5+ years in the same process family

• Docker, Git and experience writing tests

• Hands-on experience with SAP or other ERPs and TMS/WMS platforms

• Advanced Excel skills

Process

• Task-based engagement paid per task, with each task taking about 60 to 75 minutes

• Vetting task instead of a live interview

• Tasks are reviewed by the client before approval



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