I am a Computer Science graduate from Florida Institute of Technology with 2 years of experience in software development, specializing in Java, MySQL, Actimize and web technologies like HTML, CSS, JavaScript, and React. I am passionate about building secure, high-performance applications and have worked on dynamic projects focused on scalability and security. Currently, I am expanding my skills in AWS, Privileged Access Management (PAM), and Identity Access Management (IAM) to stay at the forefront of modern technology solutions.

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Skills

C++

Python

Java

Restful API

Git

DevOps

AWS

HTML

CSS

JavaScript

jQuery

MySQL

PAM

IAM

Mphasis Limited – Software Engineer (September 2021 – July 2023)

Tools & Technologies: Java, Spring Boot, HTML, CSS, JavaScript,, MySQL, Actimize AML-SAM, AIS, RCM

Participated in developing a secure, high-performance banking platform for First Republic Bank through complex coordination and advanced technological integration.
Backend Development & Frontend Integration: Built robust backend components and dynamic frontend interfaces using Java, HTML, CSS, and JavaScript,MySQL improving user experience and functionality.
Developed custom models and SAR (Suspicious Activity Report) forms tailored to meet regulatory compliance requirements.
Contributed to the Risk Management and Compliance Technology (RCT) suite, supporting an intelligent risk detection and reporting system.
Implemented Actimize AML-SAM solutions for anti-money laundering (AML) and suspicious activity detection using a comprehensive library of analytical models.
Worked with Actimize Integrated Surveillance (AIS) and Risk Case Manager (RCM) to execute models, generate alerts, and manage follow-up actions.
Leveraged the Actimize Customer Due Diligence (CDD) solution to implement a risk-based approach for AML compliance, streamlining customer risk assessment and lifecycle management.
Ensured end-to-end customer lifecycle risk management, covering data collection, identity verification, risk assessment, and case management.
Focused on minimizing customer impact while maintaining regulatory compliance through dynamic, risk-based processes.

Key Activities:

Customized and enhanced Actimize RCM and AIS objects to meet client-specific requirements, improving functionality and usability.
Conducted strategic analysis of client data and created precise specifications for tailored risk management solutions.
Actively contributed to project planning, milestone management, and continuous skill development, ensuring timely delivery.
Recognized for innovative problem-solving and proactive project management, significantly improving user satisfaction and operational efficiency.

Recipe Finder – Full-Stack Web Application

Developed a full-stack MERN application that allows users to manage a recipe database with features to initialize the database, search for recipes by name, ingredients, or description, and display results in a responsive card layout. Designed the backend using Node.js and Express for data retrieval and manipulation with MongoDB, while the frontend utilized React for a dynamic interface, including controlled form components, recipe cards, and detailed recipe views. Implemented an add-recipe feature with an ingredient auto-suggestion and dynamically updating ingredient lists. Added a favorites system to manage and view favorite recipes, with functionality to remove items from a dropdown list. The application was deployed on AWS EC2 for live access.

Handwritten Digit Recognition using Convolutional Neural Networks

Developed a CNN model to identify the digit '9' from the MNIST dataset using Python, TensorFlow, and Keras. Designed and implemented the CNN architecture, performed image preprocessing with OpenCV, and trained the model to extract key features for accurate predictions. Built a real-time prediction interface using Tkinter, enabling interactive digit recognition. Integrated error detection for multiple digits, ensuring precise single-digit classification. Demonstrated skills in deep learning, image processing, and model deployment using NumPy, OpenCV, and Jupyter Notebook.

Development of a Flutter-Based Agriculture Management Application

Developed DigiFarmer, a cross-platform mobile application using Flutter, Dart, TensorFlow Lite, and LGBM Classifier to provide farmers with AI-driven insights. The app offered features like market price tracking, inventory management, crop monitoring, and real-time weather updates, along with real-time disease diagnosis and crop quality monitoring, even in low-connectivity areas. Ensured secure user authentication, cross-platform compatibility, and GDPR/CCPA-compliant data encryption, aiming to help farmers optimize operations, manage risks, and boost productivity and profitability.

Hello, I am

Pragathi Kanala

About Me