Ayushi Prajapati

Responsible for developing, optimizing, and maintaining robust backend systems and APIs for a UGC platform, ensuring scalability and performance.

• Developed and maintained scalable backend APIs (Node.js, SQL, Sequelize, Redis) to enable seamless integration with React.js components, collaborating with frontend teams on payload structures and product requirements.
• Optimized database performance by refactoring SQL queries and Sequelize models, significantly enhancing data retrieval speed and API response times.
• Refactored and unified APIs into robust, modular endpoints (e.g., moderation, fetch, filter, pagination), reducing latency, improving maintainability, and enabling faster frontend rendering.
• Built data-driven backend features for the Analytics Dashboard, delivering critical insights (Top Performing Posts, Top Influencers, Most Active Users, Post Sentiment Analysis) and implementing PDF export functionality.
• Implemented comprehensive error-handling, input validation, and authentication, ensuring secure and reliable APIs and improving route readability and traceability.
• Integrated CI/CD pipelines with GitHub Actions for automated testing and deployment, reducing manual effort and minimizing production errors.
• Proactively resolved critical production bugs and supported ongoing feature maintenance, enhancing post-fetching mechanisms and addressing real-time user issues.
• Collaborated cross-functionally with product teams to deliver backend solutions, ensuring data consistency and scalable architecture across the UGC platform.

Responsible for extracting, analyzing, and interpreting large datasets to drive business intelligence and strategic decision-making.

• Extracted and analyzed large datasets using SQL, Python, and Excel to generate actionable insights and business intelligence for marketing and product teams.
• Maintained relational databases to ensure data accuracy; conducted Exploratory Data Analysis (EDA), tracked key performance metrics, and contributed to data-driven strategic decision-making.

An end-to-end machine learning project focused on predicting customer churn and providing actionable insights.