Key Strengths

Demonstrated proficiency in MERN stack development through the 'PocketNotes' project.
Experience with front-end technologies including ReactJS, HTML, CSS, and JavaScript.
Exposure to AI/ML concepts through projects like 'WeatherPredictionUsingAI' and 'Disease-Detection-using-AI', indicating a broad technical interest.
Practical application of Firebase in the 'MyRoommateFinder' project.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards personal projects, including full-stack web applications and AI-related initiatives. This indicates a self-starter mentality and a passion for learning new technologies. However, the lack of team-based projects or open-source contributions makes it difficult to assess collaboration and cultural fit within a structured team environment. The current role at ValueCreed as 'Developer Full-stack' aligns with the target role, but no details are provided about the responsibilities or team dynamics.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's project descriptions suggest an ability to complete personal projects, but there is no information on collaboration, problem-solving approaches, or communication within a team context.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Samridhi Dubey

Developer Full-stack

https://www.opentalent.in/samridhi-dubey

Technical Consultant @ValueCreedLLP | Full-Stack Developer

ValueCreed

Hyderabad, TelanganaMember since June 12, 2026

https://www.opentalent.in/samridhi-dubey

Top Skills

CSSHTMLJavaScriptJupyter Notebook

Skills

CSSHTMLJavaScriptJupyter Notebook

Experience

ValueCreed

Developer Full-stack

June 12, 2026 – Present

Projects

outreach-ai

April 18, 2026 – Present

Chrome extension that generates personalized LinkedIn DMs using your resume and Claude AI

View Project

MyRoommateFinder

October 26, 2024 – October 26, 2024

Roommate Finder is a web application built with HTML, CSS, ReactJS, and Firebase. This platform helps users find compatible roommates by matching them based on preferences and interests. With a 90% satisfaction rate from initial testing, it features user profiles, search functionality, and responsive design for optimal user experience.

View Project

PocketNotes

September 28, 2024 – September 28, 2024

Full-stack web app for creating, organizing, and sharing notes. Built with MERN stack: MongoDB, ExpressJS, ReactJS, NodeJS. Allows users to categorize and collaborate on notes seamlessly. Achieved a 40% increase in user collaboration. Deployed via Vercel for easy access.

View Project

Key Strengths

Demonstrated proficiency in MERN stack development through the 'PocketNotes' project.
Experience with front-end technologies including ReactJS, HTML, CSS, and JavaScript.
Exposure to AI/ML concepts through projects like 'WeatherPredictionUsingAI' and 'Disease-Detection-using-AI', indicating a broad technical interest.
Practical application of Firebase in the 'MyRoommateFinder' project.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit