Vice President - Decision Science

Role Overview: As a key member of the Analytics & Decision Science department, you will be responsible for setting up and managing credit risk management and fraud risk management frameworks and strategies. Your role will involve overseeing a team focused on developing, implementing, and refining risk management rules and collection strategies to support digital lending initiatives. Your strong analytical, strategic, and technical skills, along with a deep understanding of risk management in the lending domain, particularly within NBFCs, banks, or fintech organizations, will be crucial for success in this position. Key Responsibilities: - Lead, mentor, and manage a team of analysts and data scientists specializing in credit risk, fraud detection, and collection strategies. - Design and implement credit risk management rules and models for digital lending to ensure a robust credit risk assessment. - Define risk segmentation strategies and establish differential pricing models for various risk profiles to facilitate profitable growth. - Conduct portfolio analysis to monitor and control exposure across different lending products, ensuring adherence to risk appetite limits. - Develop and implement fraud detection and prevention strategies using advanced analytics and machine learning techniques. - Create robust fraud risk management policies integrating 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, tailoring approaches for different customer segments. - Collaborate with operations and customer service teams to ensure the effective deployment of collection strategies. - Utilize advanced analytics to continuously monitor collections performance and adjust 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 necessary to enhance risk management capabilities. - Ensure compliance with regulatory standards and best practices in risk management, credit underwriting, and collections. Qualifications Required: - Masters or Postgraduate degree in Finance, Economics, Statistics, Data Science, or a related field. - Minimum of 10 years of experience in credit risk, fraud risk management, or collections strategy within the lending industry, with a substantial focus on 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 the 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 in managing and motivating a high-performing team with a collaborative approach to cross-functional work.,