Job Summary:
We are looking for a highly analytical and collaborative Operational Research Specialist to join our Workforce Management team. This role combines deep expertise in scheduling algorithms (e.g. using FICOMosel) with strong operational research capabilities to drive data-driven decision-making and workforce optimization. The ideal candidate will be proficient in SQL, Excel, and Python (or similar languages), and have experience coordinating cross-functional projects.
Key Responsibilities:
- Design, implement, and optimize scheduling algorithms using languages like FICOMosel to meet service level and efficiency goals.
- Apply operational research techniques such as linear programming, integer programming, simulation, and queuing theory to solve complex workforce and operational challenges.
- Develop and maintain automated scheduling models and decision-support tools.
- Analyze large datasets using SQL and Excel to monitor and improve generated output and processes.
- Collaborate with stakeholders to coordinate and lead projects related to workforce optimization and operational efficiency.
- Translate business problems into mathematical models and present actionable insights into leadership.
- Continuously improve scheduling processes through innovation and automation.
Skills must to have:
- Programming skills in Python, R, or similar languages.
- Strong foundation in operational research methods and mathematical modeling.
Nice to have Required Skills & Qualifications:
- Proven experience with scheduling algorithms (FICOMosel or similar optimization languages).
- Proficiency in SQL and Excel for data analysis and reporting.
- Demonstrated ability to coordinate and manage projects across teams.
- Excellent problem-solving and analytical thinking skills.
- Strong communication and interpersonal skills; a team player who thrives in collaborative environments.
- Ability to work independently and manage multiple priorities in a fast-paced setting.
Preferred Qualifications:
- Experience in a contact center or customer service environment.
- Familiarity with WFM platforms (e.g., Verint, NICE, Genesys).
- Experience with simulation tools (e.g., Any Logic, Simul8) or optimization solvers (e.g., CPLEX, Gurobi).
- Knowledge of forecasting methodologies and real-time adherence tools.
Education and specific Training
- Higher Education Degree in Applied Mathematics with strong curriculum in Operational Research
Experience (MUST):
- Minimum 1 Year experience in:
Programming in Python, R, or similar languages;Applying operational research methods and mathematical modeling.
