Manager - Data Science

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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 opportunities
- 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 clear, 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 clear and structured manner
- Support decision-making through data-backed recommendations