Duties/Day to Day Overview
Key Responsibilities:
Operational Modeling: Develop analytical models that translate operational demand forecasts into resource and staffing requirements. Apply queueing and capacity models (e.g., Erlang) to estimate staffing needs, service levels, and performance under varying demand scenarios. Support capacity planning by analyzing demand patterns, service targets, and operational throughput across service and R&D testing.
Data Analysis & Reporting: Analyze operational and workforce-related datasets to identify trends, staffing gaps, and performance opportunities. Deliver reports and dashboards that provide visibility into key operational metrics.
Operational Analytics & Reporting: Provide analytical support to Operations leadership by developing models, dashboards, and insights that inform staffing strategies, operational readiness, and capacity planning. Build and maintain dashboards that track key operational performance indicators, staffing coverage, and service performance.
Data Processing & Data Quality: Use SQL and Python or equivalent to extract, clean, and transform large operational datasets from multiple systems. Ensure data accuracy and consistency across reporting and analytical models.
Operational Efficiency Analysis: Identify patterns, inefficiencies, and opportunities within operational data. Provide analysis that supports improved staffing allocation, operational coverage, and service performance.
Ad-Hoc Operational Analysis: Perform targeted analyses to support operational initiatives, evaluate staffing scenarios, and answer key business questions related to operational performance.
Top Requirements
(Must haves)
Qualifications:
Education: Bachelor’s or Master’s degree in Data Science, Statistics, Operations Research, Economics, Engineering, or a related field.
Experience
- 5+ years of experience in data analysis, operations analytics, or similar analytical roles
- Strong proficiency in SQL for data extraction, transformation, and analysis
- Experience using Python and Pandas for data manipulation and analysis
- Experience building dashboards with Looker, Tableau, Databricks, or similar visualization tools
Skills & Competencies
- Strong analytical mindset with a focus on solving operational problems through data
- Ability to translate complex datasets into clear, actionable insights
- Ability to build analytical models that support operational planning and capacity analysis
- Strong attention to detail and commitment to data accuracy
- Excellent communication skills, with the ability to explain technical concepts to a diverse, non-technical audience.
Additional Qualifications
(Nice to Haves)
Bonus Qualifications:
- Experience working with Workforce Management platforms such as NICE, UKG, or similar systems
- Experience building staffing models, capacity planning models, or operational forecasting models
- Experience working with large-scale operational or service-based environments
- Familiarity with fleet operations, service operations, or contact center environments