Workforce Management (WFM), Data Analytics - Monee Credit

About The Team

The Data Analyst in the Workforce Management (WFM) team plays a key role in turning operational data into actionable insights that improve workforce efficiency and service delivery. This role supports business functions such as Collections, KYC, and Customer Service, ensuring that data-driven decisions lead to better forecasting, resource planning, and overall performance. In addition to reporting and dashboarding, the analyst is expected to identify trends, propose operational improvements, and contribute to data projects that solve real-world business challenges. This position offers the opportunity to deepen analytical capabilities and gradually expand into Python and RStudio-based analysis.

Job Description

Analyze historical and live operational data to support workforce planning, staffing, and efficiency monitoring. Build, maintain, and improve dashboards and reports that track KPIs for Collections, KYC, and CS operations. Work closely with WFM and RTFM to support scheduling, forecast validation, and performance monitoring. Perform deep-dive analyses to uncover root causes, surface insights, and recommend improvements to workforce or operational processes. Collaborate with stakeholders in business teams to translate operational questions into structured data analysis. Contribute to continuous improvement projects by turning data insights into proposals and pilots. Ensure data accuracy, consistency, and integrity in all reporting and analytics outputs. Begin expanding analysis using Python and RStudio, supported by the WFM team’s upskilling roadmap.

Requirements

Bachelor’s degree in Statistics, Mathematics, Computer Science, Business Analytics, or related fields. Proficient in SQL, with hands-on experience in Presto and/or Spark. Strong analytical skills with the ability to interpret and visualize data clearly. Familiarity with spreadsheet tools (Google Sheets, Excel) and at least one BI tool (e.g., Tableau, Looker, Power BI). Strong sense of curiosity, initiative, and willingness to explore improvement ideas using data. Comfortable working cross-functionally and communicating findings with non-technical stakeholders. Organized and detail-oriented, especially in managing datasets, logic documentation, and repeatable workflows Excellent communication and interpersonal skills. Ability to work collaboratively in a fast-paced environment. Proficient in database management tools (SFTP, HUDI, Spark, etc), Python, R Studio is a big plus