AVP - Data Analytics

• Lead and drive the development and execution of analytics strategies across Tata Capital.
• Direct and guide team members while overseeing all aspects of team management to ensure effective collaboration and task completion.
• Promote a data-driven decision-making culture by identifying areas to implement analytics solutions to solve business problems
• Apply sophisticated statistical techniques to design and develop advanced analytical scorecards for customer lifecycle management, spanning across customer acquisition, cross-sell, portfolio management, collections & customer engagement
• Engage with senior management and business stakeholders to drive business growth through the effective use of analytical solutions
• Conduct thorough portfolio analyses and deep dives into various segments and cohorts to derive actionable insights.
• Work closely with business users to implement and monitor scorecards/solutions, assessing their impact on business performance and risk.
• Should demonstrate extensive knowledge of the business functioning and remain abreast of evolving industry trends.
• Manage relationships with credit bureaus and leverage them to gather market trends and insights.
• Evaluate alternate data & conduct POCs for better decision making within the organization
• Track and evaluate the effectiveness of implemented projects
• Periodic Model Monitoring & Management & recalibration basis requirement
• Lead / Mentor other team members to ensure on-time & high quality analytical projects

Qualifications & Experience

• Post Graduate degree with a background in Statistics, Mathematics, Economics, Engineering, MBA from premier institutes
• Experience of 8-12 years in the field

Leadership Competencies:

• Good interpersonal & presentation skills
• Excel in interpreting complex data using statistical techniques and machine learning for strategic insights.
• Proficient in Multi-tasking projects, ensuring timely delivery of results.
• Ability to apply creative problem-solving to tackle abstract challenges effectively.
• Should have knowledge on industry trends and regulations for informed decision-making.
• Ability to identify areas where analytical solutions can be implemented
• Should be self-driven with thought leadership

Functional Competencies

• Hands on experience with scoring/data modelling
• Tools: SAS, R or Python
• Statistical Techniques: Logistic Regression, Segmentation, Forecasting, Machine Learning Techniques, Optimization

Key Decisions taken

• Determine the appropriate statistical techniques and machine learning algorithms to be utilized in designing advanced analytical scorecards for customer lifestyle
• Decide on the segmentation and cohort analysis approaches to gain deep insights into various customer segments and portfolios.