Manager - Data Science - Analytics - Mumbai - Lodha (I-Think Techno Campus) - MM
Tata Capital · Mumbai
Main Accountabilities
1. Business Problem Understanding & Approach Development
- • Engage with Business, Credit, Risk, Marketing, HR, and Audit teams to understand problem statements
- • Participate in cross-functional discussions to understand processes and identify analytical opportunities
- • Translate business requirements into structured analytical approaches and solution frameworks
2. End-to-End Project Ownership
- • Own delivery of analytics projects from problem definition to implementation and monitoring
- • Manage timelines, stakeholder expectations, and delivery quality
- • Ensure solutions are aligned with business objectives and decision-making needs
3. Data Preparation & Variable Creation
- • Extract, clean, and prepare data from multiple sources
- • Perform feature engineering and create relevant variables for model development
- • Ensure data quality, consistency, and readiness for analysis
4. Model Development & Analytical Solutions
• Build models for use cases such as customer segmentation, credit risk assessment, early warning signals, collections prioritization, cross-sell and propensity modelling
- • Apply appropriate statistical and machine learning techniques
- • Ensure models are robust, interpretable, and aligned with business use
5. Business Analysis & Insight Generation
- • Conduct detailed data analysis to identify trends, patterns, and performance gaps
- • Generate insights to support decision-making across lifecycle stages
- • Translate analytical outputs into clear, actionable business recommendations
6. Model Scoring & Performance Tracking
- • Perform regular model scoring (monthly / periodic) to classify accounts into high, medium, and low risk categories
- • Track model performance and stability over time
- • Identify shifts in model behavior and recommend recalibration where required
7. Implementation & Deployment Coordination
- • Work closely with IT and data teams to deploy models into production systems
- • Ensure smooth integration of models into business processes and workflows
- • Validate outputs post-deployment to ensure accuracy and usability
. Monitoring & Continuous Improvement
- • Monitor performance of deployed models and analytics solutions
- • Assess whether models continue to be relevant and effective over time
- • Identify improvement areas and drive enhancements based on business feedback and data trends
9. Stakeholder Communication & Presentation
- • Present analysis, models, and insights to business and functional stakeholders
- • Explain methodologies and outputs in a clear and structured manner
- • Support decision-making through data-backed recommendations
10. Cross-Functional Collaboration
- • Work closely with Business, Credit, Risk, Marketing, HR, Audit, and IT teams
- • Ensure alignment between analytics solutions and operational execution
- • Act as a bridge between technical analytics and business application
11. Implementation & Deployment Coordination
- • Coordinate with business and technology teams for deployment and implementation of analytical solutions
- • Monitor implementation progress and ensure successful integration into business processes
- • Lead and guide junior team members in analytical problem solving, model development, and interpretation of business insights
- • Support capability building and knowledge sharing within the analytics function