Varutri Parihar

Data Scientist | Machine Learning & Deep Learning Specialist

Kolkata, IN.

About

Final-year B.Tech Computer Science student with over 2 years of hands-on experience, specializing in Machine Learning, Deep Learning, and Computer Vision. Proven ability to build end-to-end ML systems and production-ready pipelines using tools like DVC and MLflow, evidenced by two IEEE conference publications. Seeking to apply strong analytical, engineering, and research skills to impactful data science challenges.

Education

Kalinga Institute of Industrial Technology

Bhubaneswar, Odisha, India
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Bachelor of Technology (B.Tech.) Computer Science Grade: CGPA-8.85

Courses

Operating System (OS)

Computer Organisation and Architecture (COA)

Software Engineering (SE)

Object-Oriented Programming (OOP)

Database Management (DBMS)

Statistics

Probability

Publications

Precision Diagnosis of PCOS Using Machine Learning

IEEE ICCCNT 2024

Developed a diagnostic tool for PCOS using real-world health data, applying Gradient Boosting to achieve 90.16% accuracy with strong clinical metrics. This research's effectiveness led to its publication at the 15th IEEE ICCCNT 2024.

Loan Repayment Prediction Using Ensemble Learning

IEEE ICCCNT 2024

Developed a credit risk prediction system using real-world financial data, employing Stacking Classifiers to achieve 99.76% accuracy and surpass traditional models. The robustness of this system led to its publication at IEEE ICCCNT 2024, in collaboration with faculty and peers.

Skills

Programming Languages

Python, Java, C, JavaScript, HTML, CSS.

Libraries and Frameworks

NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, OpenCV, MediaPipe, NLTK, Flask, Streamlit, Dialogflow, TensorFlow, PyTorch, Keras, Scipy, FastAPI, AI Frameworks, Langchain, RAG, FAISS.

Machine Learning & AI

Supervised Learning, Unsupervised Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP), Time Series Forecasting, Hyperparameter Tuning, Model Evaluation, HuggingFace Transformers, Sentence Transformers.

Data Analysis and Visualization

Exploratory Data Analysis (EDA), Feature Engineering, SQL, Power BI, Data Cleaning, Data Forecasting.

MLOps & Deployment Tools

MLflow, DVC, Optuna, CI/CD, Git, GitHub, Dagshub.

Projects

Conversational AI Assistant

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Summary

Developed an end-to-end RAG-powered chatbot with Streamlit UI, designed to provide personalized Q&A and meal suggestions for a café environment.

Swiggy Delivery Time Prediction

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Summary

Built a reproducible ML pipeline to predict food delivery times, focusing on data preprocessing, feature engineering, and model optimization.

Hybrid Recommender System

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Summary

Engineered a hybrid recommender system using Spotify data, combining content-based and collaborative filtering to enhance personalization and content diversity.

Virtual Drawing Board with Hand Tracking

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Summary

Engineered a real-time hand tracking system for a gesture-controlled virtual drawing board, integrating computer vision techniques for natural human-computer interaction.

Data Analysis of IPL dataset

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Summary

Developed an interactive Power BI dashboard to analyze 9 years of IPL match events, providing insights into player performance and team trends.