Jyothsna Darla
Professional Summary
Python Backend Developer with 0 years of experience building RESTful APIs and backend services using Python, Flask and Django. Strong foundation in data structures, SQL and ML fundamentals; experienced in designing scalable endpoints, optimizing database queries, and delivering reproducible ML pipelines to support web and data-driven applications.
Technical Skills
Work Experience
- Designed and implemented RESTful APIs using Django and Python to serve web application endpoints, improving data retrieval efficiency by 25% through streamlined business logic.
- Collaborated in Agile sprints with Git/GitHub for code review and CI-friendly integration, reducing production bugs reported during deployment cycles by 15%.
- Optimized MySQL queries and added appropriate indexing, reducing average query execution time and improving API response performance for backend services.
- Implemented request validation, structured error handling, and centralized logging to increase API reliability and simplify debugging during development.
- Created Postman collections and unit/integration test cases for core endpoints, accelerating QA cycles and catching regressions earlier in the pipeline.
- Authored README and endpoint documentation to support handover and faster onboarding for front-end and QA teams.
- Developed a Random Forest-based Wind Energy Prediction model using scikit-learn, applying feature engineering to improve prediction performance on historical weather datasets.
- Constructed reproducible data preprocessing pipelines with Pandas and NumPy, reducing data cleaning time by 30% for large environmental datasets.
- Performed model evaluation with cross-validation and hyperparameter tuning to improve robustness and decrease overfitting on validation sets.
- Prepared reproducible Jupyter notebooks and organized model inference scripts to facilitate handover and downstream deployment activities.
- Collaborated with peers using Git for version control of datasets and model code, and documented end-to-end evaluation processes for maintainability.
- Visualized feature importance and error distributions to drive iterative feature selection and communicate model behavior to stakeholders.
Projects
- Developed a Flask web application that predicts traffic flow using NLP techniques (TF-IDF) and Random Forest models to analyze traffic-related text and historical data.
- Integrated OpenStreetMap (Nominatim) APIs and Folium to retrieve geospatial data and visualize predictions on interactive maps for user queries.
- Automated data preprocessing and prediction pipelines, reducing end-to-end processing time by 25% through batch transforms and caching.
- Optimized SQLite queries and data access patterns, improving historical traffic lookup responsiveness by 20% for the application.
- Implemented a full-stack News Portal using Django's MVT architecture with SQLite for content storage and management.
- Built user authentication and role-based access control to support administrators, authors, and readers with secure content workflows.
- Improved Django ORM queries and indexing strategies to reduce article retrieval time by ~20% for common listing and search operations.
- Developed a responsive Bootstrap-based UI to ensure consistent access across desktop and mobile devices.
Education
Certifications
Achievements
- Solved 800+ coding problems: Solved 800+ problems across LeetCode and CodeChef, demonstrating strong problem-solving and DSA practice.
- Research paper accepted at ICCIC 2025 — 2025: Paper accepted on technical innovations in Computer Science.
- Top 2 - College coding challenge: Ranked among the Top 2 participants in a college-level coding competition.
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