Senior Workforce Management Analyst

Job Track Description

The Data Science Analyst – Workforce Management plays a key role in analyzing and optimizing workforce planning, forecasting, and operational efficiency through advanced data science techniques, AI applications, and machine learning models. The role is responsible for identifying process improvements, developing analytical tools, and implementing automation solutions that enhance overall WFM effectiveness across multiple business segments.

This role requires expertise in data modeling, programming, and AI-driven analytics to transform WFM processes, enhance decision-making, and improve cost efficiency while ensuring optimal workforce allocation.

Main Requirement:

1. Fluent in Python (preferred) or R (acceptable)

Secondary:

1. Experience with data science tools (Jupyter Notebook, NumPy, TensorFlow, PyTorch, Pandas, Prophet, or similar)

1. Experience with time series forecasting libraries, such as: Darts, tsfresh, GreyKite, or similar

1. WFM or Call Center experience is a plus but not a requirement

General Profile

Performs advanced data analysis and predictive modeling to support workforce planning strategies.
Works independently with minimal supervision, delivering high-quality analytical solutions.
Applies machine learning, AI, and automation techniques to enhance WFM capabilities.
Effectively collaborates with cross-functional teams to implement AI-driven solutions for workforce management.
Identifies process inefficiencies and provides innovative solutions to improve workforce performance.
Demonstrates strong problem-solving skills and data-driven decision-making abilities.

Functional Knowledge

Strong expertise in data science methodologies, statistical modeling, and workforce analytics.
Proficiency in machine learning, AI applications, and advanced programming (Python, R, SQL, etc.).
Experience in ETL processes, data visualization (Power BI, Tableau), and automation.
Knowledge of workforce planning, forecasting, and capacity management in a BPO/call center environment.
Familiarity with WFM performance data structures (e.g., Global Table F, Centralized Hiring Plan).
Understanding of AI-driven workforce optimization techniques.

Business Expertise

Experience in Workforce Management (WFM) analytics, including capacity planning, forecasting, and shrinkage analysis.
Understanding of business financials, including contribution margin, cost efficiency, and workforce cost analysis.
Ability to align data science insights with business objectives to drive operational improvements.
Experience working in multi-site, global workforce management environments.

Impact

Drives efficiency improvements by implementing AI-powered workforce analytics and automation.
Reduces operational costs through data-driven decision-making and improved staffing models.
Enhances forecast accuracy and scheduling effectiveness using predictive analytics.
Improves overall workforce productivity, adherence, and operational performance.

Leadership

Acts as a subject matter expert in data science and AI-driven workforce management.
Provides guidance on best practices for data analytics and automation.
Mentors team members on advanced analytics techniques and AI applications.
Collaborates with cross-functional teams to drive data-driven decision-making.

Problem Solving

Uses advanced statistical models and machine learning techniques to solve workforce planning challenges.
Conducts root cause analysis on WFM performance gaps and develops AI-driven solutions.
Identifies bottlenecks in WFM processes and implements automation for improved efficiency.
Works with large datasets to generate insights and recommendations for workforce strategy.

Interpersonal Skills

Strong communication and collaboration skills to work with WFM, Operations, and IT teams.
Ability to translate complex data findings into actionable business insights.
Works effectively with global teams and cross-functional stakeholders.
Capable of presenting data-driven recommendations to senior management.

Responsibility Statements

Develops AI-powered analytics solutions to optimize workforce planning and scheduling.
Conducts complex data analysis to enhance WFM decision-making.
Builds and maintains machine learning models to improve forecasting accuracy.
Automates workforce reporting and analytics using Python, SQL, and other tools.
Manages solution configuration standards for WFM data analysis and reporting.
Collaborates with IT and Operations teams to implement AI-driven workforce solutions.
Monitors workforce performance trends and provides actionable recommendations.
Participates in special projects to integrate AI and data science into new business segments.

Education & Experience:
Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or related fields (Master's degree preferred).
3 years' experience in Data Science, WFM Analytics, or a similar role in a BPO/call center environment.
Proven expertise in machine learning, AI, and workforce analytics.

Technical Skills:
Programming: Python, R, SQL, or other relevant languages.
Machine Learning & AI: Experience in predictive modeling, deep learning, and automation.
Data Visualization: Power BI, Tableau, or equivalent.
Big Data & Cloud: Familiarity with AWS, Google Cloud, or other cloud platforms.