Manager - Data Science - Analytics - Mumbai - Lower Parel - MM

. 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

8. 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