Assistant Manager, Digital Collections Stack Analyst-

Job Purpose

The Digital Collections Stack Analyst. This position is pivotal to our mission of effectively managing delinquent accounts through digital collections stack, while enhancing our digital collection strategies.

• In this role, the primary responsibilities will revolve around identifying accounts based on the required strategy, creating, executing, and monitoring campaigns, tracking their performance, and reporting. Developing effective collections strategies for the UAE portfolio and helping the local collections unit in Pakistan and Egypt develop effective strategy will be a crucial aspect of the role. The incumbent will help manage delinquency flows and ensure that our approach remains both customer-centric and business-centric, driven by data.
• As a Digital Collections Stack Analyst, the focus will be on engaging with delinquent accounts using our digital collections stack. Through meticulous portfolio analysis, tailored digital collection strategies will be developed along with the line function and implemented to recover payments from customers who are behind on their accounts. This role is vital for maintaining the financial health of our organization and ensuring that we can assist our customers in effectively managing their obligations.
• Analytical skills, attention to detail, and strategic thinking will be highly valued in this role. Additionally, the candidate will work closely with the Digital Collections squads to further develop the features of our digital collections stack and expand its reach to other regions.

Key Result Areas

• Assist Digital Collections with data preparation and maintenance, ensuring data accuracy and accessibility for operational needs.
• Ensure timely delivery of Collections MIS reports and other analytical reports to support the collections team in decision-making.
• Act as the primary point of contact for all ad-hoc data requests related to collections, facilitating streamlined data retrieval and usage.
• Identify, design, and implement internal process improvements such as automation of manual workflows, optimization of data pipelines, and infrastructure enhancements for greater scalability and efficiency.
• Build and maintain the infrastructure required for seamless extraction, transformation, and loading of data from multiple sources using SQL and AWS big data technologies.
• Collaborate with executive leadership, product teams, data teams, and design teams to address technical challenges and improve data-driven strategies for collections and portfolio analysis.
• Implement best practices for securing sensitive collections data, ensuring compliance with data privacy regulations and company policies.
• Partner with data and analytics experts to enhance the functionality of data systems, enabling refined analysis for portfolio segmentation, delinquency management, and digital collection strategies.
• Leverage digital collections technologies to analyze delinquent accounts, design proactive engagement strategies, and improve the efficiency of collections workflows.
• Work closely with the Digital Collections squads to further develop the features of our digital collections stack and expand its reach to other regions.

Knowledge, Skills and Experience

• Minimum 4-5 years of experience in Collections / Collections Strategy / Credit Operations / Product Management
• Good understanding of Collections process and procedures
• Ability to read and interpret data and retrieve meaningful trends
• Knowledge in data architecture, defining data retention policies, monitoring performance and advising any necessary infrastructure changes
• Solid development skills in Java/ Scala / SQL / SAS
• Clear hands-on mastery in big database systems - Hadoop ecosystem, Cloud technologies (AWS, Azure, Google), in-memory database systems (HANA, Hazel cast, etc) and other database systems - traditional RDBMS (Terradata, SQL Server, Oracle), and NoSQL databases
• Comfortable in dashboard development (Tableau, Powerbi, Qlik, etc) and in developing data analytics models (R, Python, Spark)
• Bachelor's degree in computer science or equivalent; Masters preferred
• Minimum of 2-3 years' hands-on experience with data and MIS reporting
• Practical knowledge across data extraction and transformation tools