Operation Research Engineer

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.

Are you excited about applying advanced mathematical techniques to solve real-world optimization challenges? Do you enjoy working at the intersection of data science, software engineering, and operations research? If you're passionate about creating innovative solutions that drive impactful decision-making, this role could be for you. 

What this role is:

As an Operations Research Engineer on the Workforce Engagement Management (WEM) Decision Science Team, you will design, develop, and implement advanced optimization models and algorithms to solve complex workforce planning and scheduling problems. You will work in a dynamic and collaborative environment, driving innovation and building state-of-the-art solutions for large-scale operational challenges. 

What you’ll bring to the table:

To succeed, you should have a deep understanding of mathematical optimization, strong analytical skills, and the ability to design scalable solutions for intricate problems. You will collaborate with software engineers, data scientists, and product managers to deliver cutting-edge features that enhance workforce engagement and operational efficiency. 

Some details about what you’ll do:

• Research, design, and implement optimization models for workforce planning, scheduling, and resource allocation. 

• Develop innovative algorithms for solving deterministic, stochastic, and robust optimization problems. 

• Collaborate with software engineering teams to integrate optimization models into scalable, production-grade systems. 

• Work closely with data science teams to incorporate machine learning and data-driven insights into optimization processes. 

• Build prototypes to demonstrate the feasibility and value of proposed solutions. 

• Conduct rigorous testing and validation of optimization algorithms to ensure performance, scalability, and accuracy. 

• Analyze complex operational problems, identify opportunities for improvement, and deliver innovative solutions. 

• Present findings, methodologies, and results to stakeholders, demonstrating the value of optimization in workforce management.

• Contributes to the creation and maintenance of documentation.

• Stay updated on the latest advancements in operations research, mathematical modeling, and decision science. 

Requirements:

• Bachelor’s or Master’s …