Help & Supportcareers@gravityer.com
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AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
basketball-player-recognition
June 8, 2026 – Present
AI pipeline for basketball player detection, tracking, and jersey number recognition using YOLO11 + ByteTrack + EasyOCR
View Projectmultimodal-rag-chatbot
May 5, 2026 – Present
Multi-Modal RAG Chatbot that allows users to upload multiple PDFs and interact with documents using AI-powered context-aware question answering built with FastAPI, LangChain, FAISS, and OpenAI APIs.
View Projectcustomer-churn-prediction
April 8, 2026 – Present
Machine Learning project to predict telecom customer churn
View ProjectPaisabazaar-Fraud-CreditScore-Analysis
August 23, 2025 – August 23, 2025
Machine learning project analyzing credit score and fraud detection using EDA & multiple ML models (Random Forest, XGBoost, SVM, etc.).
View ProjectNETFLIX-MOVIES-AND-TV-SHOWS-CLUSTERING
August 6, 2025 – August 6, 2025
Unsupervised ML project analyzing and clustering Netflix Movies & TV Shows using EDA, TF-IDF, and 5 clustering algorithms (KMeans, Agglomerative, DBSCAN, MeanShift, OPTICS) to uncover content patterns, trends, and business insights.
View ProjectCredit-Card-Fraud-Detection
June 19, 2025 – June 19, 2025
A machine learning project for detecting credit card fraud using Random Forest, SMOTE, and evaluation metrics.
View ProjectMovie-recommendation-system
March 20, 2024 – June 18, 2025
You can get recommandations of movies related to the movie you enter (this is made python and sentimental analysis)
View Projectbook_store_website
March 10, 2024 – June 18, 2025
Exclusively for developers and programmers
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and demonstrate a strong interest in various data science and machine learning applications. The diversity of projects (RAG chatbot, churn prediction, fraud detection, clustering, computer vision, recommendation systems) suggests a broad curiosity and willingness to explore different domains. However, the lack of team-based projects or professional experience makes it difficult to assess collaboration or cultural alignment within a corporate setting. The target role is 'Data Scientist', and the projects align well with the technical requirements of such a role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a focus on technical execution.