Manager - Data Science - Analytics - Mumbai - Lower Parel - JM
- LocationMumbai, Maharashtra, India
- Work typeNot stated
- EmploymentFull-time
- Posted6 November 2026
- SourceTata Capital's careers page (Oracle Recruiting)
Live checkFirst seen 1 h ago; still listed on Tata Capital's careers page 1 h ago.
Moves fastWhen Tata Capital takes a role down early, it is usually about 4 days after posting. Apply soon.
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Check my fitAbout the role
Main Accountabilities
1. Business Problem Understanding & Approach Development
• Engage stakeholders 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. Model Development & Analytical Solutions
• Apply appropriate statistical and machine learning techniques to solve business problems
• Ensure models are robust, interpretable, and aligned with business use
3. 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
4. End-to-End Project Ownership
• Own delivery of analytics projects from problem definition to implementation and monitoring
• Manage timelines, stakeholder expectations, and delivery quality
5. Model Scoring & Performance Tracking
• Perform regular model scoring (monthly / periodic) to classify accounts into categories such as high, medium, and low risk
• Track model performance and stability over time
• Identify shifts in model behaviour and recommend recalibration where required
6. 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
7. 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
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