AVP - Analytics & Decision Science

Position Summary The ideal candidate will play a key role in setting up and managing our credit & Fraud risk management frameworks and strategies. They will oversee a team responsible for developing, implementing, and refining risk management rules and collection strategies to support our digital lending initiatives. This position requires strong analytical, strategic, and technical skills, as well as a deep understanding of risk management in the lending domain, specifically within NBFCs, banks, or fintech organizations. Key Responsibilities  Lead, mentor, and manage a team of analysts and data scientists focused on credit risk, fraud detection, and collection strategies.  Design and implement credit risk management rules and models for digital lending, ensuring robust credit risk assessment.  Define risk segmentation strategies and establish differential pricing models for varying risk profiles to support profitable growth.  Conduct portfolio analysis to monitor and control exposure across various lending products, ensuring adherence to risk appetite limit.  Develop and implement fraud detection and prevention strategies using advanced analytics and machine learning techniques.  Create robust fraud risk management policies, incorporating rule-based and behavioral analytics to identify potential fraud patterns.  Define and implement data-driven collection strategies to optimize recovery and minimize losses  Develop scorecards and segmentation models to prioritize collections efforts, customizing approaches for different customer segments.  Collaborate with operations and customer service teams to ensure effective deployment of collection strategies.  Use advanced analytics to continuously monitor collections performance, adjusting strategies to maximize recovery rates.  Develop and maintain Python-based models and scripts to automate risk and fraud analytics processes.  Work closely with product, compliance, technology, and operations teams to ensure credit and fraud risk strategies align with business objectives and regulatory requirements.  Collaborate with external partners and vendors, as needed, to enhance risk management capabilities.  Ensure compliance with regulatory standards and best practices in risk management, credit underwriting, and collections. Core Skills & Experience  Master’s or Postgraduate degree in Finance, Economics, Statistics, Data Science, or a related field.  Minimum of 10 years in credit risk, fraud risk management, or collections strategy within the lending industry (NBFCs, banks, fintechs), with significant experience in digital lending.  Proficiency in Python for data analysis, model development, and automation of risk strategies.  Familiarity with data visualization tools (e.g., Tableau, Power BI) and statistical tools (e.g., R, SAS) is a plus.  In-depth understanding of credit and fraud risk management frameworks, digital lending processes, and industry best practices.  Strong quantitative and analytical skills, with a demonstrated ability to interpret complex data and translate findings into actionable strategies.  Excellent written and verbal communication skills to effectively present insights and strategies to technical and non-technical stakeholders.  Proven experience managing and motivating a high-performing team, with a collaborative approach to cross-functional work.