Data Scientist-KMPL Support Services-Analytics

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.