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AVP - Data Analytics

Job Description

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.

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