Data Scientist Machine Learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
jd-resume-analyzer-crewai
January 29, 2026 – Present
Multi-agent JD–Resume match analyzer using CrewAI
View Projectrag_based_text_to_sql_system
August 19, 2025 – August 25, 2025
This notebook contains code for a text-to-SQL system, allowing users to fetch information from the database using natural language instead of writing SQL queries manually. It also incorporates the RAG (Retrieval-Augmented Generation) technique.
View ProjectFinancial_QA_System
August 18, 2025 – August 18, 2025
Implemented Financial QA system using RAG methodology with Langchain
View ProjectAll-My-Projects
December 10, 2021 – March 28, 2023
Whatever Projects i worked on using different ML/CV/NLP algorithms all are available at this repo
View Projectcustomer_segmentation
April 2, 2021 – April 2, 2021
Customer Segmentation (Multiclass classification) using different ML classification algorithms
View ProjectNamed-Entity-Recognition-BILSTM-CRF
January 22, 2021 – January 22, 2021
Named-Entity-Recognition-BILSTM-CRF — GitHub repository
View Projectintent_classification
October 5, 2020 – October 5, 2020
intent_classification — GitHub repository
View Projectsentiment_analysis
September 9, 2020 – September 9, 2020
sentiment_analysis — GitHub repository
View Projectresume_parser
September 9, 2020 – September 9, 2020
Same as CV Summarizer with different dataset
View ProjectCultural Fit Analysis
The candidate's projects indicate a strong focus on personal learning and exploration within the Data Science domain. The diversity of ML/NLP projects suggests an eagerness to experiment with different techniques. However, without information on collaborative projects, team roles, or communication styles, a comprehensive cultural fit analysis is not possible. The projects are primarily personal, which limits insight into collaboration and team dynamics.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are brief, and there are no psychometric test results or interview notes.