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Omnifold

AI-driven supply chain forecasting and optimization

Applied AI

Pre-Sales Solution Engineering +1Confirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • At least 2 years of experience as a Data Scientist or Applied AI Scientist.
  • Prior experience as a data scientist or selling a product that required a foundational understanding of machine learning.
  • Experience using Python and SQL to answer complex questions and solve business problems.
  • Project management skills and attention to detail.
  • Business intuition paired with technical rigor.
  • A hands-on builder mindset and willingness to learn new technologies or topics as needed.
  • Confidence engaging with business and technical stakeholders.

Responsibilities

  • Engage directly with customer problems to understand data and operational challenges.
  • Clearly frame customer problems.
  • Lead technical and value-oriented demonstrations for technical and non-technical stakeholders.
  • Work hands-on with data using Python and SQL.
  • Build custom demonstrations and prototypes to support go-to-market activities.
  • Serve as a trusted technical partner during evaluations, pilots, and implementations.
  • Support active customer deployments to ensure customers realize the platform’s full value.

About the Company

Omnifold

AI-driven supply chain forecasting and optimization

Omnifold.ai uses artificial intelligence to help large and fast-growing brands and multinational companies manage supply chains and investment decisions. Its AI systems analyze data to predict demand and optimize plans for inventory, production, procurement, logistics, and marketing. The company relies on self-improving AI that learns from new data to improve forecasts and recommendations over time. By giving organizations better visibility and forward-looking guidance, Omnifold.ai aims to reduce waste, lower costs, and improve reliability in supply chains and investment outcomes. The goal is to help clients anticipate future needs, make smarter choices, and execute plans more effectively in a complex global market.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Not listed
Founded
2024

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