Responsibilities: Data Strategy & Governance: - Design and execute the company's data strategy and roadmap, including data governance, data quality, and data management to support business goals and competitive positioning. - Establish and enforce data governance principles, practices, policies, and standards to ensure data quality, integrity, and compliance. - Define and oversee the data lifecycle management process, ensuring effective management of data from creation to archiving or deletion. Risk & Fraud Detection: - Develop predictive models to identify potential credit risks, detect fraud, and optimize credit limit assignments. Business Insights & Decision-Making: - Collaborate with business stakeholders to identify data needs and drive data-driven decision-making. - Establish a strong data-driven approach across the organization. - Drive innovation through AI, ML, and predictive modeling, leveraging modeling techniques to analyze and present actionable data for business decisions. - Oversee business intelligence (BI) and analytics initiatives to generate insights and enhance decision-making in risk management, marketing, and customer service. - Utilize data analytics to optimize pricing strategies, balance sheet management, and profitability projections. - Implement strategies to enhance customer lifetime value (CLV) through data-driven decision-making. Customer & Market Insights: - Develop and manage data analytics platforms and tools to gain insights into customer behavior, credit risk, and market trends to drive marketing campaigns, improve retention, and enhance customer experience. - Leverage data for customer segmentation, targeting, and personalization to improve marketing and engagement. Data Governance & Security: - Lead the development and maintenance of a comprehensive data governance framework across the organization. - Oversee data collection, storage, and maintenance, ensuring accuracy and accessibility. - Drive data innovation and analytics initiatives to uncover business insights and opportunities. - Lead data warehousing and integration efforts, consolidating data from multiple internal and external sources for comprehensive analysis. - Mitigate risks related to data privacy and ensure ethical handling of customer data. - Work closely with the Chief Information Security Officer (CISO) to ensure robust data security and protect against breaches or misuse. Collaboration & Leadership: - Work closely with Marketing and Product Development teams to utilize data insights for improving product offerings, pricing strategies, and customer acquisition efforts. - Lead and manage data teams, including data analysts, data engineers, and data scientists. - Stay updated on industry trends and emerging technologies to leverage data for competitive advantage. Applicants Should Possess the Following Attributes: - Expertise in developing risk models for fraud detection and credit risk mitigation. - Proficiency in customer segmentation, behavioral analysis, and targeted marketing strategies. - Strategic Thinking Ability to anticipate risks and align risk management strategies with long-term objectives. - Leadership Skills Strong leadership to manage diverse teams and influence cross-functional stakeholders. - Analytical Expertise High-level analytical capabilities to assess complex risk scenarios, conduct thorough analysis, and derive actionable insights. - Regulatory Knowledge Deep understanding of industry regulations and risk management best practices to ensure compliance and governance. - Decision-Making Strong data-driven decision-making skills to manage crises and recommend sound risk mitigation strategies.

Mumbai

Assistant Vice President - Data Analytics & Governance - FinTech 

Job Description for Assistant Vice President - Data Analytics & Governance - FinTech  in NA in  Mumbai for (8-20) years of experience. Apply Now!