Data Science Analytics - Loans/ Credit Card !!

Job description

Role & responsibilities • Business Analytics & Strategy • Develop and execute analytics strategies to drive growth across unsecured lending and credit card businesses. • Generate actionable insights on customer acquisition, portfolio performance, risk behavior, and profitability. • Partner with Product, Business, Risk, and Technology teams to drive data-led decision making. • Identify opportunities to improve customer conversion, engagement, retention, and cross-sell outcomes. • Data Science & Machine Learning • Lead the development and deployment of predictive models across the lending lifecycle. • Build and enhance models related to customer acquisition, propensity, cross-sell, churn, fraud, and portfolio management. • Drive implementation of ML/AI-based solutions to improve business performance and customer experience. • Ensure continuous monitoring, validation, and refinement of analytical models. • Portfolio & Customer Analytics • Analyze customer behavior, transaction patterns, and portfolio trends to improve portfolio quality and profitability. • Design segmentation frameworks and customer targeting strategies. • Monitor key portfolio metrics and recommend corrective actions based on trends and emerging risks. • Stakeholder Management • Influence senior leadership through data-driven insights and strategic recommendations. • Collaborate closely with Product, Risk, Digital Banking, Marketing, and Technology teams. • Present analytical findings and business recommendations to executive stakeholders. • Technology & Analytics Enablement • Drive adoption of modern analytics tools, cloud-based analytics platforms, and automation frameworks. • Promote best practices in data governance, model development, and analytics delivery. • Mentor and build high-performing analytics teams. Preferred candidate profile • 8-15 years of experience in Analytics, Data Science, Digital Lending, Cards Analytics, or Consumer Finance Analytics. • Strong experience within Unsecured Lending and/or Credit Cards domain is mandatory. • Experience in Digital Banking, Fintechs, NBFCs, Credit Card issuers, or Retail Banking analytics functions preferred. • Strong knowledge of machine learning techniques and predictive modelling. • Hands-on experience with analytics tools such as Python, SQL, SAS, R, Power BI, Tableau, or similar. • Deep understanding of customer analytics, portfolio analytics, decision science, and data modelling. • Experience working with large datasets and modern data platforms. • Strong problem-solving and analytical skills. • Strategic thinking with business acumen. • Ability to translate complex analytics into business outcomes. • Excellent stakeholder management and communication skills.