AVP - Collection Strategy

The core responsibilities for the job include the following:
End-to-End Collection Strategy Design:
Develop and optimize data-driven collection strategies across the pre-due stage, early bucket collections, late bucket collections, and recovery and write-off management.
Design stage-wise treatment strategies to maximize resolution rates and minimize roll-forward.
Risk and Portfolio Analytics:
Conduct in-depth portfolio analysis to identify risk trends, delinquency drivers, and behavioral patterns.
Develop and monitor portfolio scorecards.
Perform risk segmentation to enable differentiated strategy deployment.
Analyze large historical datasets to extract actionable insights and improve collection efficiency.
Advanced Data and AI/ML Implementation:
Develop and deploy AI/ML models for delinquency prediction, roll rate forecasting, recovery propensity, and contactability optimization.
Partner with data engineering teams for seamless data integration and model deployment.
Evaluate model performance, stability, and recalibration needs.
Strategy Performance Monitoring:
Design performance dashboards and KPIs for collection effectiveness.
Monitor employee scorecards aligned with productivity, efficiency, and compliance.
Conduct champion-challenger testing to continuously optimize strategies.
Big Data and Data Interpretation:
Work with large, complex structured and unstructured datasets.
Perform cohort analysis, roll-rate analysis, vintage analysis, and behavioral segmentation.
Interpret historical performance data to refine future strategy design.
Stakeholder Collaboration:
Collaborate with Risk, Operations, Product, Technology, and Senior Leadership teams.
Present analytical findings and strategic recommendations to leadership.
Requirements:
Master's or bachelor's degree in engineering, computer science, IT, data science, statistics, mathematics, economics, or a related quantitative discipline.
Preferred education from premier institutions such as IIT, IIM, ISI, or other top-tier institutes.
4-8+ years of relevant experience in collections analytics, credit risk, or financial services.
Technical Skills:
Strong proficiency in SQL, Python / R, advanced Excel, and data visualization tools (Power BI / Tableau).
Deep understanding of: portfolio scorecards, risk segmentation methodologies, Employee performance scorecards, roll rate and vintage analysis, AI/ML model development and validation, and big data ecosystems and data integration frameworks.
Core Competencies:
Strong analytical and problem-solving skills.
Strategic thinking with business acumen.
Deep understanding of credit risk and collections lifecycle.
Ability to interpret complex datasets and convert insights into executable strategies.
Excellent communication and stakeholder management skills.
Preferred Attributes:
Experience in the NBFC/banking/FinTech collections environment.
Exposure to regulatory compliance in collections.
Hands-on experience with large-scale portfolio management.
Proven track record of driving measurable improvement in collection efficiency and recovery rates.

Experience
6-10 yrs