Disruption Optimization Scientist (Remote & Flexible)

SITA; Barcelona; Híbrido; EUR 70.000 - 95.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flex Week

Flex Day

Flex-Location

Employee Wellbeing

Professional Development

Competitive Benefits

Descripción de la vacante

SITA is hiring an Optimization Scientist in Barcelona to design and build disruption-recovery engines for airline operations. You will handle end-to-end solver development, translating complex airline rules into efficient optimization models and producing production-ready code.

The role emphasizes collaboration with engineering teams and domain growth, with a focus on scalable solutions. Ideal candidates bring strong mathematical optimization skills, experience with Gurobi/CPLEX/SCIP, and

Formación

• Strong foundation in mathematical optimization and operations research.
• Hands-on experience with commercial solvers (Gurobi/CPLEX/SCIP).
• Proficiency in Python and SQL, production-quality coding.
• Ability to translate complex business rules into algorithms.

Responsabilidades

• Own disruption-recovery solver pipeline end-to-end—from formulation to production code.
• Translate airline rules into solver formulations (crew legality, routing, rebooking).
• Validate solver solutions against disruption cases with Solutions Experts.
• Monitor KPIs for solution quality and runtime; balance trade-offs.
• Extend solver capabilities and ship new optimization features as the product evolves.
• Collaborate with Back-End and Data Engineering to integrate outputs.
• Develop deep airline-operations domain knowledge for better formulations.

Conocimientos

Mathematical optimization

Operations research

Linear programming

Mixed-integer programming

Network flow

Metaheuristics

Python

SQL

Git

Optimization libraries

Educación

MSc or PhD in OR / Applied Mathematics / CS

Bachelor's degree in a related quantitative field

Herramientas

Gurobi

CPLEX

SCIP

Git

Descripción del empleo

SITA is hiring an Optimization Scientist in Barcelona to design and build disruption-recovery engines for airline operations. You will handle end-to-end solver development, translating complex airline rules into efficient optimization models and producing production-ready code.

The role emphasizes collaboration with engineering teams and domain growth, with a focus on scalable solutions. Ideal candidates bring strong mathematical optimization skills, experience with Gurobi/CPLEX/SCIP, and