Live opening · Posted 3 days ago

Data Scientist_SUPPORT SERVICES_0789_1288_1081157

KOTAKMAMC - KTKNV20ETF · Mumbai, Maharashtra, India
Oracle
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At a glance

The key details from the original listing.

Posted 3 days ago
CompanyKOTAKMAMC - KTKNV20ETF
LocationMumbai, Maharashtra, India
SourceOracle
ListedPosted 3 days ago

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About the role

Description supplied by the original job listing.

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 Responsibilities
1. 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.

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