VP/AVP - Data Analytics & Governance

Role & Responsibilities:

Key highlights of the role are listed below (purely indicative and not limiting):

• Design and execute the company's data strategy and roadmap, including

data governance, data quality, and data management to support the

companys 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 behaviour, 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, behavioural 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