Optimisation AI Scientist

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 about 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 mathematical models - objective functions, costs, penalties, and constraints

• Configure and run optimisation models for customer pilots and implementation, and support Solutions Architects in delivering results and debriefs

• Build and run Python models against third-party solvers across multiple dataset scales, and benchmark results across use cases

• Work with Engineering and Data Science leads to define the path to production-grade solver integration and customer specific implementations within Pigment's architecture

• Engage technically with solver vendor teams during partnership evaluation

Who you are and what you can do:

• Demonstrable experience formulating and solving optimisation problems for real-world operational use cases

• Proficiency in Python with hands-on experience in a major solver library (Gurobi, OR-Tools, CPLEX, HiGHS, or equivalent)

• Experience with supply chain/operations data — SKUs, BOMs, capacity constraints, service levels, lead times, inventory targets etc.

• Understanding of core OR techniques: branch-and-bound, LP relaxation, constraint programming, sensitivity analysis

• Degree in Operations Research, Applied Mathematics, Industrial Engineering, CS, or related field (MS/PhD advantageous)

#LI-HYBRID

#LI-LS1

\n\n

We conduct background checks as part of our hiring process, in accordance with applicable laws and regulations in the countries where we operate. This may include verification of employment history, education, and, where legally permitted, criminal records. Any checks will be conducted lawfully, with candidate consent, and information will be treated confidentially.

 

Pigment is an equal opportunity employer. We believe diversity is a strength and fosters innovation. We are committed to enabling everyone to feel included and valued at the workplace.  All qualified applicants will receive consideration for employment without regard to age, color, family, gender identity, marital status, national origin, physical or mental disability,  sex (including pregnancy), sexual orientation, social origin, or any other characteristic protected by applicable laws. We may process your personal data in accordance with our HR Data Protection Notice.