Scheduling Optimization Engineer

Applaudo; Distrito Capital; A distancia; VES 450.000 - 675.000; Jornada completa

Descripción de la vacante

A leading software development company is seeking a data-driven professional to solve complex scheduling and resource allocation challenges. You will develop and maintain optimization models, applying advanced techniques to improve efficiency. The ideal candidate has hands-on experience with optimization solvers and strong analytical skills. This position offers a flexible work environment and numerous perks to reward dedication and excellence.

Servicios

Work from home

Flexible schedule

Private medical insurance

Great work environment

Formación

• Advanced knowledge of optimization modeling techniques.
• Hands-on experience with optimization solvers.
• Strong analytical and modeling skills.

Responsabilidades

• Develop and maintain optimization models for scheduling.
• Collaborate with teams to align outputs with needs.
• Analyze results for efficiency and cost improvements.

Conocimientos

Optimization modeling

Scheduling model development

Solver experience (Gurobi, CPLEX, OR-Tools)

Programming (Python, Julia, C++)

Data analysis

Problem-solving

Communication skills

Descripción del empleo

Job Description

About You

You are a data-driven professional passionate about solving complex scheduling and resource allocation challenges. You thrive on applying advanced optimization techniques to real-world problems, balancing mathematical rigor with practical feasibility. With strong analytical and modeling skills, you design solutions that improve efficiency, reduce costs, and ensure compliance with operational and regulatory requirements.

You bring to Applaudo the following competencies:

• Advanced knowledge of optimization modeling (integer programming, constraint programming, heuristics/metaheuristics).
• Proven experience developing and maintaining large-scale scheduling models in applied environments.
• Ability to incorporate operational rules, contractual agreements, regulatory requirements, and business constraints into model formulations.
• Hands-on experience with optimization solvers (e.g., Gurobi, CPLEX, OR-Tools).
• Proficiency in programming languages such as Python, Julia, or C++.
• Strong understanding of data analysis for planning based on event calendars, service times, passenger volumes, and destination planning.
• Analytical mindset with strong problem-solving skills and attention to detail.
• Excellent communication skills to work effectively with technical and non-technical stakeholders.

You will be accountable for the following responsibilities:

• Develop and maintain advanced optimization models to solve large-scale scheduling problems.
• Build models that consider event calendars, service times, passenger volumes, and destinations using available data.
• Integrate operational rules, contractual obligations, regulatory requirements, and business constraints into model formulations.
• Apply optimization solvers (Gurobi, CPLEX, OR-Tools) to generate feasible, efficient schedules.
• Collaborate with operations, planning, and technology teams to align outputs with real-world needs.
• Analyze results to identify cost savings, efficiency improvements, and compliance risks.
• Continuously refine models to adapt to changes in resource availability, demand patterns, and operational constraints.

Additional Information

At Applaudo Studios, values such as trust, communication, respect, excellence, and teamwork are our keys to success. We believe in working with the best and treating each other with respect and admiration.

Apply today and join the Best Digital team in the region! We appreciate the hard work of our team and offer perks designed to thank them for their commitment and excellence.

Some of our perks and benefits include:

• Work from home
• Flexible schedule
• Celebrations
• Special discounts
• Entertainment area
• Flexible workspaces
• Great work environment
• Private medical insurance
• Benefits may vary according to location and availability. Please request further information when applying.