Optimisation AI Scientist at Pigment | England, GB | Rezi

Optimisation AI Scientist at Pigment

Optimisation AI Scientist

Pigment · England, GB

1 months ago

Optimisation AI Scientist

Pigment · England, GB

a month ago
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About the Role

Own the technical delivery of Pigment's solver pilot program and build the foundations of a production-grade optimization capability, moving customers from descriptive planning to prescriptive, solver-driven decision-making. This role is partially customer-facing, involving the formulation of client optimization problems and direct implementation involvement.

Responsibilities

  • Formulate supply chain optimization problems as rigorous mathematical models, including objective functions, costs, penalties, and constraints.
  • Configure and run optimization models for customer pilots and implementation.
  • Support Solutions Architects in delivering results and debriefs.
  • Build and run Python models against third-party solvers across multiple dataset scales.
  • 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.

Requirements

  • Demonstrable experience formulating and solving optimization 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, including SKUs, BOMs, capacity constraints, service levels, lead times, and inventory targets.
  • Understanding of core OR techniques such as branch-and-bound, LP relaxation, constraint programming, and sensitivity analysis.
  • Background checks are conducted as part of the hiring process in accordance with applicable laws and regulations.
  • Checks 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.

Skills

  • Python
  • Gurobi
  • OR-Tools
  • CPLEX
  • HiGHS
  • Optimization
  • Mathematical Modeling
  • Supply Chain Optimization
  • Operations Research
  • Applied Mathematics
  • Industrial Engineering
  • Computer Science

Location

  • Paris
  • London
  • New York
  • Toronto
  • San Francisco
  • Austin

Work Type

  • Hybrid

Education Level

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

About the Company

  • Founded in 2019, Pigment is a fast-growing SaaS company redefining business planning and performance with an AI-powered platform.
  • Pigment empowers organizations across diverse industries like Consumer Packaged Goods, Retail, and Technology to integrate data, people, and processes for rapid planning and adaptation.
  • The company has over 500 professionals across North America and Europe.
  • Pigment has secured nearly $400 million in funding from leading global venture capitalists.
  • Recognized as a Visionary in the 2024 Gartner® Magic Quadrant™ for Financial Planning Software.
  • Partners with industry leaders such as Unilever, Vinci, Kayak, Siemens, and Coca-Cola.
  • Champions smart risks, celebrates bold ideas, and challenges the status quo.
  • Fosters an environment of collaboration, excellence, strong performance, and proactivity with humility.

Equal Opportunity

  • Pigment is an equal opportunity employer.
  • Believes diversity is a strength and fosters innovation.
  • 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.
  • May process personal data in accordance with its HR Data Protection Notice.