Build and deploy analytical models for banks, NBFCs, and insurers. Develop scalable model pipelines, conduct exploratory data analysis, create feature repositories, and maintain model lifecycle configurations. Develop predictive models for credit risk and customer personalization, identify cross-sell and up-sell targets, monitor model performance, and communicate results to stakeholders to support business adoption.
Role Data Scientist/Sr Data Scientist Business: Not Applicable Department: Analytics Sub-Department: Not Applicable Location: Mumbai Role
As a Data Scientist specializing in to building Analytical Models for Banks/NBFCs/Insurance industry, your primary responsibility is to utilize machine learning algorithms or statistical models to optimize Business Processes across Customer Life Journey. You will be required to build the model pipeline, work on its deployment and provide the required support until its last leg of adoption. Your role involves collaborating with cross functional teams to develop predictive models that assess Credit Risk and/ or personalize Customer Experience. You will also be responsible for identifying relevant base for targeting (cross-sell/up-sell) and running these campaigns from time to time.
Key Responsibilities1. Writing Optimized Code:
- Develop and maintain efficient, scalable code for model pipelines
- Implement best practices in coding to ensure performance and resource optimization
2. Version Control and Lifecycle Configuration:
- Familiar with best practices to manage codebase changes with available resources
- Maintain and update configuration files to manage the lifecycle of data science models
3. Extracting Usable Information from Data:
- Translate business needs into data-driven solutions and actionable insights
- Conduct thorough exploratory data analysis to uncover trends and patterns.
- Create and maintain feature repositories to document and manage features used in models
4. Building Robust Models:
- Develop models that are reliable and generalize well across different time periods and customer segments.
- Continuously monitor and improve model performance to adapt to changing data and business conditions
5. Publishing Model Outcomes:
- Communicate model results and insights effectively to stakeholders.
- Facilitate the adoption of models by ensuring they meet business needs and are user-friendly.
Kotak Mahindra Bank Mumbai, Maharashtra, IND Office
Mumbai, India
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