Data Science with 4+ years in Data Science, Machine Learning & AI
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Data Scientist with 4+ years of experience in Data Science, Machine Learning, NLP, and Generative AI solutions across diverse business domains. Expertise in building and deploying end-to-end AI applications, including RAG-based systems, deep learning models, and analytical solutions. Skilled in collaborating with cross-functional stakeholders, gathering requirements, and transforming business needs into AI-driven solutions. Proficient in Python, SQL, Power BI, SSRS, Metabase, and cloud platforms (Azure, AWS) for delivering actionable insights and automation.
BHARAT UNIVERSITY
Bachelor of Technology
January 1, 2017 – January 1, 2021
SWIFT SOLUTION PRIVATE LIMITED
Data Scientist
September 1, 2021 – Present
India
RAG-based Assistant for Epics & Stories Retrieval
May 6, 2026 – Present
Developed a Retrieval-Augmented Generation (RAG)-based application integrated with an open-source LLM to provide employees with epics and related stories for software development queries. Collaborated with scrum masters, product owners, and architects to curate epics and stories dataset. Extracted epics and stories using JSON Character Text Splitter and generated embeddings using OpenAI Embeddings. Stored embeddings in Azure Cosmos DB for scalable and fast retrieval. Built a two-way pipeline: If a user query matches stored embeddings → retrieved relevant epics/stories. If no match → generated responses using an open-domain LLM. Improved software team productivity with quick, context-aware answers.
Legal Document Type Classification
May 6, 2026 – Present
Developed an NLP-based machine learning application to automatically classify legal documents (e.g., Agreement, Invoice, Deed, Policy) for legal tech document automation, reducing manual effort and improving document management efficiency. Collaborated with legal experts to curate a labeled dataset of legal documents across multiple categories. Performed text preprocessing: tokenization, lemmatization, stop-word removal, and created custom legal dictionaries. Converted documents into numerical representations using TF-IDF and experimented with Bag-of-Words and embeddings. Built and evaluated multiple ML classifiers (Logistic Regression, Random Forest, XGBoost) and experimented with Neural Networks for improved performance. Fine-tuned hyperparameters using GridSearchCV and implemented cross-validation for robust performance. Deployed the model in Azure ML for scalable, real-time document classification. Created analytics dashboards to visualize document type distribution for legal teams.
Specifying the Top-performing Warehouses across Geographies
May 6, 2026 – Present
Developed a data-driven warehouse performance analysis system using clustering techniques to identify top-performing warehouses across geographies, enabling optimized inventory distribution and improved regional sales strategies. Extracted, cleansed, and validated data from multiple sources. Performed descriptive statistical analysis and clustering to segment warehouse performance. Provided actionable insights into retail sales patterns and customer segmentation.
Face Emotion Detection using YOLO
May 6, 2026 – Present
Developed a real-time facial emotion detection system using YOLOv8 and OpenCV to classify human emotions from live video streams, enabling applications in customer sentiment analysis, market research, and human-computer interaction. Developed a real-time facial emotion detection system using YOLO models. Designed and annotated a custom dataset for emotion classification. Fine-tuned pre-trained YOLO models and integrated OpenCV for live video stream processing. Created a user-friendly interface to visualize real-time emotion detection.
Cultural Fit Analysis
The psychometric test score of 0, which evaluates aspects like work attitude and team collaboration, raises substantial concerns about the candidate's cultural fit. This score suggests potential challenges in aligning with organizational values and collaborative work practices.
Soft Skills & Operational Fit
The candidate's psychometric test score of 0 indicates significant concerns regarding logical reasoning, work attitude, stress handling, and team collaboration. This performance suggests a potential lack of foundational soft skills critical for operational effectiveness and integration into a professional team environment.