Digital Innovation Co-op – Supply Chain

Samsara Samsara · Enterprise · CA · Remote · Operations Management

Co-op role focused on applying AI/ML to supply chain operations, including building AI agents, automation tools, and ML models for forecasting and risk detection. Involves data exploration, cleaning, and collaboration with business stakeholders.

What you'd actually do

  1. Assist in building or testing AI-powered tools that automate supply chain workflows (e.g., PO anomaly detection, logistics exception alerts).
  2. Help prototype lightweight bots or agents that connect internal tools and enterprise systems (ERP, planning platforms, Salesforce).
  3. Support evaluation and testing of LLM-based assistants for operational use cases.
  4. Contribute to ML model development for demand forecasting, inventory analysis, or risk detection.
  5. Explore and clean supply chain datasets; perform exploratory data analysis to surface insights.

Skills

Required

  • BS or MS in Computer Science, Data Science, Industrial Engineering, Supply Chain, Statistics, or a related field
  • Python for data analysis (pandas, NumPy, scikit-learn or equivalent)
  • SQL or experience querying structured datasets
  • Comfort working with ambiguous problems and iterating toward solutions
  • Strong written and verbal communication skills

Nice to have

  • Coursework or project experience in machine learning, NLP, or operations research
  • Exposure to LLMs or generative AI tools (e.g., OpenAI, Anthropic Claude, LangChain)
  • Familiarity with supply chain concepts: demand planning, inventory, procurement, or logistics
  • Experience with data visualization (Tableau, Power BI, matplotlib, Plotly)
  • Prior internship, research, or project experience in a data-focused role
  • Knowledge of ERP systems (NetSuite, SAP) or CRM platforms (Salesforce)

What the JD emphasized

  • writing real code
  • exploring messy operational data
  • seeing their work influence actual business processes
  • foundational programming skills in Python
  • interest in ML or AI applications
  • excited to apply AI/ML within real-world operational contexts
  • Proficiency in Python for data analysis
  • Comfort working with ambiguous problems and iterating toward solutions
  • shipped or meaningfully contributed to a production-grade or production-bound AI/ML feature

Other signals

  • AI Agent & Automation Development
  • Machine Learning & Analytics
  • applied AI/ML in an operational setting
  • shipped or meaningfully contributed to a production-grade or production-bound AI/ML feature