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Business Problem Understanding Approach Development
Engage stakeholders to understand problem statements
Participate in cross-functional discussions to understand processes and identify analytical prospects
Translate business requirements into structured analytical approaches and solution frameworks
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
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 transparent, actionable business recommendations
End-to-End Project Ownership
Own delivery of analytics projects from problem definition to implementation and monitoring
Manage timelines, stakeholder expectations, and delivery quality
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
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
Stakeholder Communication Presentation
Present analysis, models, and insights to business and functional stakeholders
Explain methodologies and outputs in a explicit and structured manner
Support decision-making through data-backed recommendations

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📌 Manager Data Science Mumbai (India)
🏢 Tata Capital
📍 India