Naga Nischala Chinnam

• Built ML models for disease risk prediction, patient outcome analysis, and customer segmentation.
• Developed predictive models using Random Forest, XGBoost, Logistic Regression, Gradient Boosting.
• Performed feature engineering, preprocessing, and model evaluation using Scikit‑learn.
• Collected, cleaned, transformed, and analyzed structured and unstructured healthcare data to support data-driven decision-making using Python.
• Developed interactive dashboards and reports in Power BI and Tableau to visualize insights and enhance stakeholder understanding.
• Built and deployed REST APIs using FastAPI to serve ML models.
• Worked with Azure ML for model deployment, monitoring, and storage.
• Collaborated with data engineers, developers, analysts, and product managers to deliver AI solutions.

Environment: Python, Pandas, NumPy, Scikit-learn, TensorFlow, XGBoost, FastAPI, SQL, Power BI, Tableau, Azure ML, Azure Data Factory, Git, Docker, Jupyter Notebook, Agile Scrum

• Designed and developed scalable web applications using Java, Python, and Spring Boot.
• Built RESTful APIs for product catalog, inventory, order management, and payment processing.
• Developed backend microservices and integrated third‑party payment gateways and shipping APIs.
• Optimized SQL queries, enhancing database performance for PostgreSQL and MySQL.
• Reduced API response time by optimizing business logic and database queries.
• Collaborated with UI/UX teams, integrating responsive front‑end features to enhance user experience.
• Participated in Agile Scrum ceremonies: sprint planning, backlog refinement, daily stand‑ups, retrospectives.
• Performed unit testing, integration testing, debugging, and production support.
• Used Git for version control and Jenkins for CI/CD automation.
• Coordinated with QA engineers to resolve defects, ensuring higher software quality.

Environment: Java, Python, Spring Boot, REST APIs, SQL, PostgreSQL, MySQL, Git, Jenkins, Docker, Kubernetes, Azure, Agile Scrum