Help & Supportcareers@gravityer.com
AI Data Scientist
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Louisiana at Lafayette
Data Scientist
June 29, 2026 – Present
Vectorless-Rag
March 13, 2026 – Present
Reasoning-based, vectorless RAG over a large document using a hierarchical tree (PageIndex) and a Vision-Language Model (Llama 4 Scout), no embeddings, no vector store, no text chunking.
View ProjectMultiAgent-Recommender
March 1, 2026 – Present
🎬 Conversational recommender system powered by a three-specialized-agent CrewAI pipeline (Preference Analyst → Movie Matcher → Recommendation Generator), powered by Vector search, Groq LLM, and LangGraph.
View ProjectSemantic-Cache
February 28, 2026 – Present
Semantic caching for LLM responses using Redis Vector DB, LangChain, and HuggingFace embeddings, parses PDFs, generates FAQs with Groq, and serves similarity-based answers without redundant LLM calls.
View ProjectCensus-Bureau-Project
February 19, 2026 – Present
Predictive modeling and customer segmentation using census data. Includes binary classification for income levels and unsupervised learning for marketing personas.
View ProjectWeather-MCP
October 8, 2025 – October 8, 2025
Model Context Protocol (MCP) Server and Client for a Weather app that provides real-time weather alerts and forecasts.
View ProjectConversational_AI
July 30, 2024 – September 19, 2024
Conversational_AI — GitHub repository
View ProjectNeuralNetworks
March 3, 2024 – March 7, 2024
This include project that demonstrates my deep learning skills
View ProjectImageProcessing
January 15, 2024 – January 21, 2024
This include project that demonstrates my image processing skills
View ProjectCultural Fit Analysis
The candidate's projects are predominantly personal and highly technical, focusing on cutting-edge AI/ML research and development. This indicates a strong drive for innovation and self-directed learning, which could be a good cultural fit for a research-oriented or fast-paced data science team. However, the lack of team projects or professional experience beyond a current role at a university (with no specified start date) makes it difficult to fully assess collaboration and broader organizational fit. The diversity of projects (AI, image processing, C++/graphics) suggests a broad technical curiosity.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a strong technical focus, but collaboration, communication, and problem-solving approaches in a team setting are not evident.