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Optimisation AI Scientist

CompraTica Empleos

EMP:Technology
London or Paris
Tiempo Completo
Remoto
0 vistas

Descripción

Join Pigment: Transforming Business Planning and Performance with AI     Founded in 2019, Pigment stands out as one of the fastest-growing SaaS companies globally, redefining business planning and performance with our AI-powered platform.

We empower organizations across diverse industries, including Consumer Packaged Goods, Retail, and Technology, to seamlessly integrate data, people, and processes, enabling them to plan and adapt rapidly.

    With a vibrant team of over 500 professionals across North America and Europe, and offices in Paris, London, New York, Toronto, San Francisco and Austin, Pigment has successfully secured nearly $400 million in funding from leading global venture capitalists.

Our recognition as a Visionary in the 2024 Gartner® Magic Quadrant™ for Financial Planning Software underscores our commitment to excellence, as we proudly partner with industry leaders like Unilever, Vinci, Kayak, Siemens, and Coca-Cola.

    At Pigment, we champion smart risks, celebrate bold ideas, and challenge the status quo—all as a united team.

Every team member has the opportunity to make a significant impact and tackle ambitious challenges.

Together, we pursue excellence with a collaborative spirit, continuously raising the bar to ensure strong performance and a proactive approach while fostering an environment of humility.

    If you are passionate.

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innovation and wish to collaborate with some of the brightest minds in the industry, we would love to hear from you! We are hiring an Optimisation AI Scientist to own the technical delivery of Pigment's solver pilot programme and build the foundations of a production-grade optimisation capability - moving customers from descriptive planning to prescriptive, solver-driven decision-making

This role is partially customer-facing: leading and shaping the formulation of each client's optimisation problem, directly involved in implementations.

What you will do: Formulate supply chain optimisation problems as rigorous.

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