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

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

27 Sep
|
Tata Capital
|
Mumbai

27 Sep

Tata Capital

Mumbai

. 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 explicit, 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

📌 Manager - Data Science - Analytics - Mumbai - Lower Parel - MM
🏢 Tata Capital
📍 Mumbai

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