This role focuses on developing advanced simulation solutions for clients across various industries. You'll be integral to a specialized team leveraging intelligent simulation, Digital Twins, and AI to drive data-informed decisions and enhance operational efficiency. The position involves creating Agent-Based Simulation (ABS) models that capture intricate systems, including autonomous entities, human behavior, and operational workflows.

As part of cross-functional teams, you will collaborate with simulation engineers, solution architects, AI specialists, and business consultants. Together, you will deliver innovative solutions designed to boost operational performance, resilience, and overall business outcomes. This is an opportunity to work on cutting-edge technologies that transform business operations.

- Design and implement Agent-Based, Discrete Event, and hybrid simulation models to address complex business challenges. - Translate intricate client requirements and business processes into effective simulation solutions and experimental scenarios. - Conduct thorough model verification, validation, calibration, and sensitivity analysis to ensure solution accuracy. - Analyze simulation outputs to provide clear, actionable insights to stakeholders. - Partner with engineering, analytics, AI, and business teams to deliver integrated simulation and Digital Twin solutions. - Adhere to Agile methodologies, engineering standards, and quality assurance practices throughout the project lifecycle. - Develop reusable simulation assets, comprehensive technical documentation, and valuable knowledge management artifacts.

A minimum of 3 years of experience is required in Discrete Event Simulation.

Expertise in developing and maintaining Agent-Based Simulation (ABS), Discrete Event Simulation (DES), and hybrid simulation models is essential, utilizing platforms such as AnyLogic, Mesa, GAMA, and NetLogo. Proficiency in programming languages like Python, Java, and SQL, along with a strong understanding of Object-Oriented Programming principles, is crucial for building scalable and reusable solutions.

Further requirements include the ability to design intelligent agent behaviors and simulation architectures, perform model verification and validation, and integrate simulation models with enterprise applications and data streams. Experience with cloud platforms like Azure/AWS and visualization tools such as Power BI is also beneficial.