Shaurya Cairae

1. Dynamic API Maintenance and Development for Machine Learning Models:
• Managed and enhanced Dynamic API for machine learning models utilized by multiple teams within American Express.
• Implemented features and optimizations to ensure scalability, reliability, and performance of the API.
• Collaborated with cross-functional teams to gather requirements, design solutions, and integrate new machine learning models into the API infrastructure.
• Utilized Java, Hadoop, Python, and Jupyter Notebook to develop and maintain the API, leveraging advanced Java concepts and Hadoop ecosystem tools for efficient data processing and manipulation.

2. Application Development for Matching Probabilities Score with Multiple Machine Learning Algorithms:
• Engineered a Java-based application integrated with Hadoop and Python, enabling data scientists to calculate matching probabilities scores across various machine learning algorithms.
• Leveraged advanced Java techniques and Hadoop ecosystem components for large-scale data processing and analysis.
• Developed Python scripts within Jupyter Notebook for exploratory data analysis and algorithm evaluation.
• Collaborated with data scientists to understand requirements and iteratively improve the application's functionality and performance.

• Optimized this Batch Application working on java and hadoop. Reduced running time from 40minutes(for 10,000 records) to 2 minutes.

3. API Development for PMML-Based Machine Learning Models using Spring Boot:
• Designed and developed APIs to serve PMML-based machine learning models using Spring Boot framework.
• Implemented robust and scalable endpoints for model inference, incorporating best practices in RESTful API design and security.
• Ensured seamless integration of PMML models into the API infrastructure, allowing for real-time predictions and scoring.

4. Centralized Logging Implementation using ElasticSearch for Batch Application:
• Spearheaded the implementation of centralized logging using ElasticSearch for a batch processing application.
• Designed and configured logging infrastructure to efficiently collect, index, and analyze log data generated by the batch application.
• Integrated Logstash for log ingestion and Kibana for visualization and monitoring of log data, enabling proactive troubleshooting and performance optimization.

5. Testing Automation using Python (Pandas) Scripts:
• Developed Python scripts utilizing Pandas library for automating testing processes, resulting in significant reduction in testing time for batch application.
• Implemented comprehensive test scenarios and data validation routines to ensure robustness and reliability of the batch application.
• Collaborated with QA team to streamline testing workflows and improve overall testing efficiency.

6. Unit Test Cases Development using Mockito and JUnit:
• Created unit test cases using Mockito and JUnit frameworks to validate the functionality of individual components within the application.
• Implemented mocking and stubbing techniques to isolate dependencies and ensure thorough testing coverage.
• Executed test suites regularly as part of continuous integration pipelines to maintain code quality and reliability.

7. Artifact Validation Module:
• Developed a module for validating artifacts to ensure data integrity and compliance with quality standards.
• Implemented validation routines and error handling mechanisms to identify and rectify discrepancies in artifacts.
• Collaborated with stakeholders to define validation criteria and incorporate feedback for continuous improvement.
• Utilized Java and relevant libraries/frameworks to implement validation logic and automate validation processes.

8. GitHub Folder Push Module:
• Designed and implemented a module to push folders to GitHub repositories, streamlining deployment and version control processes.
• Integrated with GitHub API to facilitate seamless folder uploads and updates across repositories.
• Implemented error handling and logging mechanisms to track deployment status and troubleshoot issues effectively.
• Collaborated with DevOps team to automate deployment workflows and ensure consistency across environments.