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Data Analyst with less than a year in Python & Machine Learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring Data Analyst skilled in Python, SQL, Excel, and Power BI with hands-on experience in data cleaning, exploratory data analysis, machine learning, and dashboard creation. Seeking an opportunity to leverage analytical and visualization skills to drive data-driven business decisions.
Kalinga Institute of Industrial Technology (KIIT)
Master of Science (M.Sc.) · Computer Science
August 1, 2024 – June 30, 2026
SVIMS
Bachelor of Computer Applications (BCA) · Computer Applications
August 1, 2020 – June 30, 2023
Instagram Follower Analysis
June 21, 2026 – Present
Analyzed engagement trends using Python and Pandas. Performed EDA and visualization to identify user behavior patterns. Created insights-driven reports for follower growth and interaction analysis.
RAG-Based AI Teaching Assistant
June 21, 2026 – Present
Developed an end-to-end Retrieval-Augmented Generation (RAG) system that converts video lectures into an AI-powered teaching assistant. Implemented automated video processing, multilingual transcription, semantic chunking, and vector embedding generation for context-aware retrieval. Designed a semantic search pipeline using cosine similarity and nomic-embed-text embeddings to deliver accurate lecture-based answers. Integrated locally hosted llama3 via Ollama for fully offline, privacy-preserving, and cost-efficient AI inference.
California Housing Price Prediction
June 21, 2026 – Present
Developed a machine learning pipeline to predict California housing prices using regression-based models and structured datasets. Performed feature engineering, preprocessing, and exploratory data analysis to improve model performance and evaluation. Built automated preprocessing workflows using Pipeline, ColumnTransformer, StandardScaler, OneHotEncoder, and SimpleImputer. Trained and evaluated Linear Regression, Decision Tree, and Random Forest models using RMSE and cross-validation techniques.
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in data analysis, machine learning, and AI, which aligns well with a data-driven culture. The diversity of projects (follower analysis, housing price prediction, AI teaching assistant) indicates a broad curiosity and willingness to explore different domains within data science. The focus on practical application and end-to-end system development suggests a results-oriented mindset. However, without information on collaboration or communication styles, a full cultural fit assessment is limited.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems, suggesting good problem-solving skills. The RAG project, in particular, shows initiative in integrating various technologies for a complete solution. However, without direct work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or other operational fit aspects.