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Data Science with 2+ years in Machine Learning & NLP
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Results-driven Data Scientist and AI Engineer specializing in Machine Learning, Generative AI, and NLP pipelines. Proficient in Python and statistical analysis, with hands-on experience designing end-to-end predictive models and scalable Retrieval-Augmented Generation (RAG) applications. Combines robust analytical problem-solving skills with a data-driven approach to transform complex datasets into actionable insights and optimized business solutions.
Edure Learning
Diploma in Data Science · Data Science
August 1, 2025 – June 30, 2026
University of Calicut
BA Economics with Foreign Trade · Economics with Foreign Trade
August 1, 2020 – June 30, 2023
IGNOU
MA Economics · Economics
N/A – June 30, 2026
Prestige Mall Management Pvt. Ltd
Customer Service Associate
January 1, 2024 – December 31, 2025
Cochin, Kerala, India
Satellite Image Classification: Hurricane Damage Detection
June 1, 2026 – Present
Developed and tested a Deep Learning CNN model to automate post-disaster damage assessment, conducting performance analysis on large-scale datasets. Troubleshot and debugged model training processes, utilizing data augmentation and dropout layers to prevent overfitting and ensure maximum efficiency. Executed predictive model evaluations to ensure robust performance on unseen geographic data, acting as a virtual simulation of environmental impact.
View ProjectDocLens: AI Document Intelligence (RAG)
June 1, 2026 – Present
Designed and developed a Retrieval-Augmented Generation (RAG) application enabling multi-PDF Q&A, automated document summarization, and answer verification for quality assurance. Engineered an end-to-end NLP pipeline orchestrating PyPDF text extraction, semantic chunking, and FAISS retrieval, ensuring optimal operational feasibility. Deployed a Streamlit UI utilizing Groq LLAMA 3.3 for precise text generation, maintaining system documentation and strict user session isolation.
View ProjectGerman Credit Risk Classification
June 1, 2026 – Present
Evaluated and upgraded 4 classification models on financial records, performing system verification and performance metric analysis (Confusion Matrix, F1-Score). Optimized Random Forest via GridSearchCV, achieving 75.5% test accuracy and applying PCA for dimensionality reduction. Designed and deployed a Tkinter GUI for real-time risk prediction, meeting specific operational requirements for end-users.
View ProjectIntroduction to Generative AI Learning Path
Google Cloud
June 1, 2026 – Present
Excel and ChatGPT
LinkedIn Learning
June 1, 2026 – Present
Microsoft Azure Data Scientist Associate (DP-100) Cert Prep
LinkedIn Learning
June 1, 2026 – Present
Data Analytics: Dashboards vs Data Stories
LinkedIn Learning
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including NLP/Generative AI, CNN for image classification, and traditional ML for credit risk, shows a broad interest and adaptability in various data science domains. The pursuit of multiple degrees and certifications indicates a strong drive for continuous learning and self-improvement. The projects are well-aligned with a Data Science target role, demonstrating initiative and practical application of learned skills. The candidate's background in Economics also provides a valuable perspective for business-oriented data analysis.
Soft Skills & Operational Fit
The candidate's previous role as a Customer Service Associate, while not directly technical, involved analyzing operational metrics, collaborating cross-functionally, and tracking customer satisfaction. These experiences suggest an ability to work with data, communicate findings, and contribute to process improvements, which are transferable soft skills for a data science role. The project descriptions are clear and highlight problem-solving and efficiency, indicating a results-oriented approach.