Data Science Engineer - AI/ML & NLP Enthusiast

Vaishnavi Reche +91-797*******

Bachelor of Technology § GitHub Profile

G.H Raisoni College of Engineering and Management, Nagpur ï LinkedIn Profile Education

•Bachelor of Technology in Data Science Engineering 2022-26 G.H Raisoni College of Engineering and Management, Nagpur CGPA: 8.26 Projects

• AceAI - Smart Interview Simulation

An interactive AI-powered interview simulation that conducts real-time mock interviews using speech and facial recognition.

– Real-time voice input with speech-to-text conversion and Gemini-2.5 flash powered dynamic question generation.

– Performance scoring system based on answer quality, confidence, emotion, and tone.

– Technology Used : React.js, Python (Flask), Google Gemini-2.5 flash, Google Speech API

• InsightBot - Data Summary Bot

A smart AI chatbot, analyzes uploaded data, answers questions, generates visualizations, and provides insights with PDF export.

– AI-powered chatbot that generates automated insights, visualizations, and smart summaries from uploaded CSV/XL- SX/ TSV/JSON files.

– Integrated local LLM (Ollama) with fallback logic, enabled natural language QA, auto-EDA, file preview, smart suggestions, and PDF report downloads via Streamlit.

– Technology Used : Python, Streamlit, Pandas, Seaborn, Plotly, FPDF, Ollama

• Multi-Agent Research Assistant

A multi-agent system that analyzes PDFs, performs web searches and fetches ArXiv papers to deliver real-time insights.

– Automated agent orchestration using a rule-based controller to route user queries to PDF RAG, Web Search, or ArXiv agents.

– Supports dynamic document summarization, research trend discovery, and scientific paper retrieval.

– Integrated with FastAPI backend and Streamlit frontend for seamless interaction and logging.

– Technology Used: Python (FastAPI, Streamlit), FAISS, Sentence Transformers, SerpAPI, ArXiv API, Groq LLM Experience

•Data Science Intern Jan 2024- Mar 2024

Acmegrade Online

– Worked on real-world datasets to perform data cleaning, exploratory data analysis (EDA), and visualization using Python libraries like Pandas, Matplotlib, and Seaborn.

– Built and evaluated predictive machine learning models (Linear Regression, Decision Trees, Random Forest) using Scikit-learn, optimizing performance with cross-validation and hyperparameter tuning.

– Applied feature engineering techniques to improve model accuracy and used correlation heatmaps and histograms for visual insights.

Technical Skills and Interests

Languages: C, C++, Python, SQL, R

Libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, NLTK, TensorFlow, Keras, Streamlit Tools: VScode, Github, Jupyter, Google Colab, PowerBI Cloud/Databases: Relational Database(MySql)

Coursework: Data Structures & Algorithms, Operating Systems, Object Oriented Programming, Database Management System, Machine Learning, Natural Language Processing Soft Skills: Problem Solving, Self-learning, Critical thinking, Adaptability Certifications

• Fundamentals of Generative AI -HCL GUVI 2024

– Completed a certified course covering core concepts of Generative AI, including large language models (LLMs), diffusion models, and real-world applications using tools like ChatGPT and DALL·E.

• R for Data Science -IBM 2024

– Completed a certified course by IBM focusing on data analysis, visualization, and statistical modeling using R, including hands-on projects with tidyverse packages and real-world datasets.

• Python for Machine Learning -Great Learning 2025

– Completed a foundational course covering Python essentials for machine learning, including libraries like NumPy, pandas, matplotlib, and scikit-learn, with practical implementation of ML algorithms.

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