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

Job Description

. 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