Overview In this role you design and implement disruption-recovery optimization engines that convert manual airline replanning into fast, automated decisions. You will own the end-to-end solver pipeline, from mathematical formulation to production code, within the OCCam Science team. You'll translate airline rules into optimization models, validate against real disruption cases, and push new functionality as the product evolves.

This is an opportunity to shape AI-powered disruption management for general aviation and work across cross-functional teams to impact airline operations at scale.

Compensaciones / Beneficios Flex Week: work from home up to 2 days/week

Flex Day

Flex-Location: up to 30 days a year remote

Employee Wellbeing programs (EAP, Champion Health)

Professional Development opportunities

Competitive benefits

Responsabilidades Own disruption-recovery solver pipeline end-to-end, from formulation to production code

Translate airline rules (crew legality, aircraft routing, passenger reaccommodation) into solver formulations

Validate solver solutions against real disruption cases with Solutions Experts

Own solution-quality and runtime KPIs, balancing quality and solve time





Extend solver capabilities and ship new optimization functionality

Collaborate with Back-End and Data Engineering to integrate solver outputs into the live product

Build deep airline-operations domain knowledge and translate it into better formulations

Requisitos principales Strong foundation in mathematical optimization and OR

Hands-on experience with solvers (Gurobi, CPLEX, SCIP)

Proficiency in Python and SQL; production-ready coding; Git

Ability to translate complex business rules into algorithms

Experience bridging OR theory and production code

Self-directed with ability to ramp up domain knowledge independently

Detail-oriented for solver debugging

Understanding of how formulation choices affect solver performance end-to-end

Degree in Operations Research, Applied Mathematics, Computer Science, Industrial Engineering or related quantitative field; MSc/PhD a plus

Self-direction

Detail-oriented

Systems thinking

Mathematical optimization (linear programming, MILP, network flows)

Large-scale optimization techniques

Metaheuristics

📌 Optimization specialist (Barcelona)
🏢 Sita - Société Internationale De Télécommunications
📍 Barcelona