Descripción del puesto

About the Role
As a Data Scientist specializing in optimization, you’ll design and implement advanced metaheuristic algorithms to solve complex operational challenges in the aviation and travel industry. You'll translate business needs into mathematical models and collaborate across teams to bring optimization solutions into production.

Key Responsibilities

• Optimization & Modelling: Design and implement custom metaheuristic algorithms (e.g., Genetic Algorithms) to solve real-world business problems. Translate complex requirements into mathematical models and constraints.

• Data Preparation & Analysis: Collect, clean, and analyze data to inform model design and enhance optimization performance. Identify patterns and improve data usability for algorithm development.

• Evaluation & Iteration: Test, tune, and evaluate algorithm performance. Conduct sensitivity analyses to assess impact of various parameters and constraints.

• Collaboration & Delivery: Work closely with product and engineering teams to integrate optimization models into production environments. Communicate findings and model implications to stakeholders.

• Mentorship & Knowledge Sharing: Support junior team members and contribute to a culture of continuous learning within the data science team.

Requisitos

Requirements

• Bachelor’s or Master’s degree in Operations Research, Applied Mathematics, Computer Science, or related fields.

• 4+ years of experience in data science, analytics, or optimization roles.

• Strong expertise in metaheuristic techniques (e.g., Genetic Algorithms, PSO, Simulated Annealing) and constraint modeling.

• Proficiency in Python and libraries such as Pandas, NumPy, Scikit-learn, SciPy, as well as optimization tools like PuLP, Pyomo, DEAP, Optuna, or Mealpy.

• Ability to translate complex mathematical and business problems into practical optimization algorithms.

• Solid understanding of data modeling and constraint programming.

Nice to Have

• Experience with linear optimization solvers (e.g., Gurobi, CPLEX, OR-Tools).

• Familiarity with ETL processes, data cleansing, and visualization tools.

• Exposure to deploying models using cloud-based infrastructure (AWS preferred).

• Basic knowledge of R or other complementary programming languages.