Lead Analyst, Workforce Management – Dialer Operations
India
Full Time
1 week ago
No Sponsorship
Key skills
JavaJavaScriptOracleSQLLeadership
About this role
Role Overview
Develop and deliver ad‑hoc and recurring reports for senior and executive leadership within the Reverse Servicing business unit.
Perform advanced data analysis/automation using SQL/PL-SQL (Oracle preferred) to identify trends, risks, and opportunities across operational and staffing metrics.
Partner with business units to manage staffing models, including work‑volume analysis, FTE forecasting, and identification of current or future staffing gaps.
Conduct root cause analysis to understand drivers behind performance, productivity, and staffing variances.
Own and manage the staffing model change request process, ensuring data integrity and timely implementation.
Design, enhance, and maintain Excel‑based forecasting and analytical models, including complex formulas, pivot tables, and automation.
Support automation of reporting and operational processes through macros or other technical solutions.
Create clear and concise PowerPoint presentations for executive management, summarizing insights and recommendations.
Work independently on multiple initiatives while delivering projects within defined timelines.
Proactively identify opportunities to improve internal operations, reporting efficiency, and customer experience.
Collaborate effectively with stakeholders across Operations, Technology, and Leadership to align analytical outputs with business needs.
Requirements
Bachelor’s degree or equivalent of fifteen (15) years of education; Computer Science, Information Technology, or related field preferred.
Exceptional SQL/PL-SQL skills required; experience with Oracle databases is strongly preferred.
Strong proficiency in Microsoft Excel and PowerPoint, with the ability to create complex analytical reports and executive presentations.
Working knowledge of Java programming language and/or web technologies (HTML, JavaScript) is considered a strong plus.
Experience with data modeling, querying large datasets, and validating data accuracy.
Knowledge of basic statistics (mean, median, standard deviation, distributions, etc.).
Strong analytical thinking, problem‑solving skills, and attention to detail.
Ability to work independently, manage ambiguity, and handle multiple priorities in a fast‑paced environment.