Sayyad Shabuddin

Client: HSBC

The project involved the development of a comprehensive system that required writing Python scripts, creating API gateways, crafting REST APIs, using AWS services, working with databases, and incorporating regulated entity data.

• Python Scripting: Developed Python scripts to meet specific requirements, incorporating AWS Lambda for efficient serverless execution. The code, driven by a deep understanding of project needs, utilized AWS Lambda for scalability.
• API Gateway Creation: Designed and implemented vital API gateways, enabling seamless system communication through AWS API Gateway.
• REST API Development: Developed REST APIs, designing endpoints and logic for efficient data exchange, while integrating with AWS Lambda for scalable serverless operations.
• Database Management: Oversaw efficient data storage and retrieval using PostgreSQL, including schema design and optimized queries for robust database management.
• Data Storage: Utilized AWS S3 for storing static files and data, ensuring scalability and efficient management within the system.

Skills: Lambda, SQS, PostgreSQL, Docker, Python3, Git, Tkinter, AWS Glue, Pyspark, Pandas, Oracle, GraphQL.

Implemented Verification service, Helped in development of its infrastructure, Via Implementation of Lambda & SQS services,

Worked on Many ETL Jobs, and Desktop Applications which will take advantages of Clean, Transformed & Standard Data and provide insights to the client, all these applications are used for Fintech.

Desktop Application DComparer:
Purpose: Data Integrity validation between Two Databases & Transformation, & Standardization.
TechStack - Tkinter, Pandas, Python, psycopg2, CX_Oracle

Desktop Application DExport:
Purpose: To Provide Database records easily with Just SQL query with output in Multiple formats such as CSV, EXCEL, TXT.
TechStack - Tkinter, Pandas, Python, psycopg2, CX_Oracle

AWS Glue ETL Applications:
Purpose: To Design a scripts which can Keep Monitor on S3 Bucket for Input files and process The Input Data, Via Pyspark, and apply all Transformation & Standard rules for the data and Load it into Aurora PostgreSQL.
TechStack - AWS GLue, AWS Aurora, Pyspark, Python, PostgreSQL

Payroll - Aidetic (Aug/2021 to Feb/2022)

Client: DeloitteThe Data Mining Project involved web scraping, database design, REST API development, and API integration. The Document Ingestion Project focused on document processing, authentication system development, front-back end integration, and deployment. These projects leveraged technologies such as Django, PostgreSQL, Docker, AWS (EC2, S3), Git, and incorporated various libraries and tools to achieve their goals in data mining and document ingestion.
Data mining Project:My Responsibilities, worked on all aspects of below area.

• Web Scraping: Selenium, Beautiful soup, Requests, Python
• Database Design: PostgreSQL, PGadmin4
• Back End/Design REST API's: Django, Asyncio
• API's Integration: Facebook, Instagram
• Deploy: Docker, AWS EC2, S3, Git

Document Ingestion Project:My Responsibilities, worked on all aspects of below area.

• Authentication System: Custom Built with django
• Front-Back End Integration: AJAX, JSON
• Back End: Django, Pptx
• Database Design: PostgreSQL
• Messaging Service: RabbitMQ
• Deploy: AWS, EC2, S3, Git

The Label Tool Project aimed to create UI APP to manage and Create datasets for machine learning models, the Face Authentication System focused on enabling authentication using face detection and recognition, and the ML Model Benchmark Automation project aimed to automate the benchmarking process of machine learning models. These projects utilized a range of technologies and techniques, including front-end and back-end development, image processing, deployment using Docker and AWS services, and integration of various libraries and frameworks.

Label Tool Project: For creating datasets for machine learning models.

My Responsibilities, worked from scratch, worked on all aspects of below area.

• Front End: JavaScript, Bootstrap, HTML/CSS
• Back End: Django, Mysql
• Image Processing: Opencv4, Pillow
• Deploy: Docker, AWS, EC2, S3, Git

Face Authentication System: Authentication system for internal teams via face detection and recognition.

My Responsibilities, worked on all aspects of below area.

• Back End: Django, Mysql, SSD, Dlib, Opencv3+
• Deploy: Docker, AWS, EC2, S3, Git

ML Model Benchmark Automation: Automating benchmarking process of machine learning models.

My Responsibilities, worked on all aspects of below area.

• Models: YOLO, SSD, FACENET, etc.
• Metrix: All point Interpolation, IOU
• Libraries: Matplotlib, Opencv3+, Pillow, JSON