• Volume Prediction Model: Analyzed market trade data to develop a volume prediction model for BNPP Global Markets, achieving 90% accuracy.• Data Preprocessing: Applied outlier detection and feature scaling to enhance data quality and model performance.• Machine Learning Implementation: Leveraged various ML models and ensemble techniques to optimize predictions.• Hyperparameter Tuning: Used Keras RandomSearch for neural network optimization.• Analytics Dashboard: Developed an interactive ServiceNow analytics dashboard with Django and Chart.js for efficient data visualization and decision-making.

• Responsibly involved in end-to-end software development cycle by making BRDs, identifying an optimal technical solution, sprint planning, delivery, and post-launch performance analysis• Worked with custom APIs handling MongoDB and tested them using Postman, which helped in reducing network errors by 20%• Built custom UI elements and animation using Rive, which enhanced the design of the application by 30%

• Completed my work ahead of time, which led to quick updates for the application• Effectively solved many existing issues in the application, which improved the application working by 30%• Collaborated with quality engineers, product management, and design teams to ensure quality in all phases of app development• Integrated third-party libraries, including Picasso, Glide, Retrofit, and Crashlytics