Mahmudur Rahman Email & Phone Number

HandyHome Hub :I created a web application using React and Redux for the front end and Ruby on Rails for the back end, allowing customers to book appointments for home services. I implemented secure user authentication with Devise JWT to ensure safe signup and login for users. The user interface was designed to be user-friendly and allow customers to view available services and book appointments within specific time slots. I also included a feature that allows users to manage their appointments, including the ability to cancel appointments at any time.Achievements:• Successfully delivered a fully functional web application that streamlined the appointment booking process for home services.• Worked collaboratively with a cross-functional team to ensure seamless integration of front-end and back-end components.• Demonstrated expertise in React, Redux, Ruby on Rails, and authentication systems.• Received positive feedback from project partners and mentors for the high-quality code and user experience.CMS - Cost Management :I created a budget app called "CMS" using Ruby on Rails, Devise, Tailwind CSS, and PostgreSQL. The app has a user-friendly interface that allows users to manage their finances easily. Users can select predefined categories or create custom ones, and then add and track expenses under each category. This provides a comprehensive budget management solution.Achievements:• Successfully delivered a feature-rich budget application with robust category management and expense tracking capabilities.• Collaborated with team members to ensure the seamless integration of front-end (Tailwind CSS) and back-end (Ruby on Rails) components.• Demonstrated proficiency in Ruby on Rails, Devise, Tailwind CSS, and PostgreSQL.• Enhanced the user experience by enabling the creation of custom categories for personalized budgeting.

• Successfully completed over 10,000 data labeling, content moderation, and quality control tasks on the UHRS platform for Micro Crowdsourcing.• Contributed to the improvement of search engine algorithms and machine learning models by annotating and evaluating data.• Collaborated with a team of 50+ independent contractors on multiple crowdsourcing projects with Appen, and met all project deadlines.

• Annotated data for machine learning and AI projects at Appen, ensuring accurate labeling and categorization of large datasets.• Collaborated with a global team of annotators to maintain high-quality annotations and meet project deadlines.

• Transcribed and converted audio recordings into written format with high accuracy as a Data Transcriber at Appen.• Met strict project deadlines while maintaining confidentiality and ensuring the utmost precision in data transcription.