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Data Science with less than a year in Machine Learning & GenAI.
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Results-driven Data Scientist with 6+ months of hands-on experience building end-to-end ML pipelines and extracting actionable insights from large-scale datasets. Proven expertise in NLP text classification, customer segmentation, and Generative AI / RAG applications across healthcare, airlines, and retail. Proficient in Python, SQL, scikit-learn, XGBoost, LangChain, Azure OpenAI, and MLflow with a strong track record in model evaluation, SHAP explainability, and stakeholder-ready reporting. Targeting Data Scientist, ML Engineer, or Gen AI / Agentic AI Developer roles in Bengaluru or Hyderabad.
Jyothy Institute of Technology
B.E. · Artificial Intelligence & Machine Learning
August 1, 2021 – June 30, 2025
Intenso Tech Solution Pvt. Ltd.
Data Scientist Intern
September 1, 2025 – March 1, 2026
Bengaluru, Karnataka, India
Adverse Event Seriousness Classification
September 1, 2025 – March 1, 2026
Built a supervised ML text classifier to categorize adverse event narratives by seriousness level, reducing manual pharmacovigilance review time and accelerating regulatory submission workflows. Extracted TF-IDF and n-gram features from clinical text; joined with SQL-sourced structured case data to create a hybrid feature matrix, improving classification accuracy on imbalanced datasets. Applied stratified cross-validation, class-weight tuning, and threshold optimization to maximize recall on the minority (serious) class, minimizing false negatives in patient safety decisions. Generated SHAP explainability reports for regulatory reviewers, surfacing top predictive features aligned with FDA documentation requirements. Deployed automated batch scoring pipelines with data drift detection; versioned all models and experiments in MLflow for full reproducibility.
GenAI Operations & Policy Assistant (RAG)
September 1, 2025 – March 1, 2026
Developed a production-ready Generative AI RAG assistant enabling airline operations staff to retrieve policy guidance and SOP information with grounded, cited answers — significantly reducing manual lookup time. Ingested and indexed operational manuals using optimized chunking strategies tailored for procedural and tabular content, improving retrieval relevance and coverage. Designed prompt templates generating concise, cited responses with confidence-based fallback logic to handle out-of-scope queries gracefully. Implemented hybrid retrieval with metadata filters for improved domain-specific search across IRROPS, baggage, and rebooking workflows. Optimized system latency and cost through targeted prompt tuning; validated results using scenario-based evaluation datasets.
Customer Segmentation - Unsupervised Machine Learning
September 1, 2025 – March 1, 2026
Applied K-Means and DBSCAN clustering on 30,000+ retail customer records; used SQL for data extraction and PCA for 2D visualization - identified 5 distinct actionable customer personas. Improved marketing campaign targeting efficiency by ~18% through segment-based insights; delivered a Power BI dashboard communicating cluster profiles and recommended business actions. Evaluated cluster quality using Silhouette Score and Davies-Bouldin Index; iterated on feature selection to maximize inter-cluster separation and intra-cluster cohesion.
View ProjectDelivered 3 end-to-end AI/ML projects: clinical NLP text classification (Nova Pharm, USA), GenAI RAG policy assistant (AeroLink Airways, APAC), and unsupervised retail customer segmentation.
Unknown
June 1, 2026 – Present
Proficient in SHAP model explainability, MLflow experiment tracking, production batch scoring pipelines, and automated data drift monitoring.
Unknown
June 1, 2026 – Present
6-Month Data Science Internship Certificate
Intenso Tech Solution Pvt. Ltd.
March 1, 2026 – Present
B.E. in Artificial Intelligence & Machine Learning
Jyothy Institute of Technology
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's projects span diverse domains (healthcare, airlines, retail) and include both professional and personal initiatives, indicating adaptability and a broad interest in applying data science. The experience with Generative AI/RAG and traditional ML demonstrates a blend of cutting-edge and foundational skills. The target role alignment with Data Scientist, ML Engineer, or Gen AI / Agentic AI Developer suggests a good fit for roles requiring a mix of research, development, and deployment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a results-driven approach, focusing on reducing manual effort, improving efficiency, and delivering actionable insights. The experience with stakeholder-ready reporting and explainability suggests an understanding of business impact and communication. The use of MLflow for reproducibility and data drift detection points to an operational mindset.