Vice President/Assistant Vice President - Data Analytics & Governance - FinTech (12-20 yrs)

Roles & Responsibilities:

- Design and execute the company's data strategy and roadmap, including data governance, data quality, and data management to support the company's 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.

- Develop predictive models to identify potential credit risks, detect fraud, and optimize credit limit assignments.

- Collaborating with business stakeholders to identify data needs and drive data-driven decision-making

- Establish a strong data-driven approach to ensure decision-making across the organization

- Drive innovation through the use of artificial intelligence (AI), machine learning (ML), and predictive modelling. Leveraging modelling techniques to identify, analyze and present actionable data to drive business decisions

- Oversee the implementation of business intelligence (BI) and analytics initiatives to generate insights and enhance decision-making across various business functions, including 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.

- Develop and manage data analytics platforms and tools to provide actionable insights into customer behavior, credit risk, and market trends in order to drive marketing campaigns, improve customer retention, and enhance overall customer experience.

- Leverage data to enhance customer segmentation, targeting, and personalization for more effective marketing and customer engagement.

- Lead the development, implementation, and maintenance of a comprehensive data governance framework across the organization.

- Oversee the collection, storage, and maintenance of data across the organization, ensuring accuracy and accessibility.

- Drive data innovation and analytics initiatives to uncover business insights and opportunities.

- Lead the data warehousing and data integration efforts to consolidate data from multiple sources (internal and external) 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 measures and protect against breaches or misuse.

- Work closely with Marketing and Product Development teams to use data insights to improve product offerings, pricing strategies, and customer acquisition efforts.

- Lead and manage data teams, including data analysts, data engineers, and data scientists

- Staying abreast of 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 the organization's long-term objectives.

- Leadership: Strong leadership skills to manage a diverse team 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 effective governance.

- Decision-Making: Strong, data-driven decision-making skills to manage crisis situations and recommend sound risk mitigation strategies.

- Proficiency in data analysis tools and techniques such as SQL, Python to generate insights and build financial models

- Strong understanding of data governance frameworks and experience with implementing data quality management practices that comply with RBI regulations, GDPR and other data privacy laws

- Business Intelligence & Reporting using BI tools for real time insights and decision support