Data Science with less than a year in AI, Machine Learning, and Data Analysis
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Assessing your cultural and operational fit
Artificial Intelligence & Data Science graduate with hands-on experience in data analysis, machine learning, and business intelligence. Skilled in Python, SQL, Power BI, and statistical modeling with experience building predictive models, performing exploratory data analysis, and developing interactive dashboards. Strong ability to transform raw datasets into actionable insights using data preprocessing, feature engineering, and visualization techniques
Dr. V R K Women's college of Engineering & Technology, Aziznagar, Moinabad
Bachelor of Technology · Artificial Intelligence & Data Science (AI&DS)
August 1, 2021 – June 30, 2025
Narayana jr. College, SRNagar
Intermediate · MPC
June 1, 2019 – May 31, 2021
Ravindra Bharathi School, SRNagar
SSC
N/A – May 31, 2019
ML Experiment Tracking and Model Management using MLflow
June 1, 2026 – Present
Built an end-to-end experiment tracking workflow using MLflow to log model parameters, metrics, and artifacts for reproducible ML experimentation. Trained and evaluated multiple Logistic Regression models with different hyperparameters on the Iris dataset using Scikit-learn. Enabled seamless model comparison and versioning through the MLflow Tracking UI, ensuring transparency and reproducibility across experiments.
Wine Authenticity Prediction using Machine Learning (SVM)
June 1, 2026 – Present
Developed a production-ready SVM classifier to distinguish legitimate wines from fraudulent ones, addressing class imbalance with class_weight='balanced'. Optimized model performance through extensive EDA, feature scaling, and hyperparameter tuning with GridSearchCV, achieving 84% accuracy and a 0.91 F1-score. Engineered a reusable prediction pipeline by serializing the final model with Pickle, enabling easy integration into a potential web application for real-time fraud detection using Streamlit.
AI Document Intelligence & Interview Question Generator using LangChain (RAG)
June 1, 2026 – Present
Developed a production-ready Generative AI application using LangChain and RAG architecture to parse resumes/ PDFs and generate contextual responses. Implemented document chunking, HuggingFace embeddings, and FAISS vector search for efficient semantic retrieval. Built an interactive Streamlit interface with real-time chat, enabling users to upload documents and receive AI- generated answers and role-specific questions.
Customer Churn Analytics
June 1, 2026 – Present
Analyzed telecom customer dataset to identify churn risk drivers and retention opportunities through segmentation and behavioral trend analysis. Built interactive Power BI dashboard tracking churn rate, tenure distribution, and customer service usage patterns. Identified high churn risk among month-to-month contract customers and high monthly charge segments. Performed exploratory data analysis using Python to uncover churn correlations across contract types and internet service categories. Generated business insights supporting customer retention strategy planning.
Monday Café Sales Analytics Dashboard
December 1, 2025 – December 31, 2025
Performed analytics on 10,000+ transactional records for multi-location retail performance monitoring. Built interactive dashboards for week-over-week performance tracking. Designed KPI monitoring system for category-level performance insights. Executed ETL workflows using Power Query ensuring structured reporting datasets. Generated insights supporting operational decision-making.
LEARNING BOT
September 1, 2024 – October 31, 2024
Designed a rule-based AI chatbot using basic NLP techniques. Implemented a simple AI chatbot that can understand and respond to basic user queries using Natural Language Processing (NLP) techniques. The chatbot will recognize user inputs and provide predefined responses based on the intent of the query.
DATA SCIENCE WITH GEN AI CERTIFICATION
Medha Edu Tech.
June 1, 2026 – Present
DATA ANALYTICS CERTIFICATION
Nirmaan.Org.
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and foundational skill set in Data Science and AI, aligning well with a target role in this field. The diversity of projects, ranging from ML model development and experiment tracking to Generative AI and business intelligence dashboards, indicates a broad curiosity and willingness to explore different facets of data science. The academic nature of all projects, however, means there's no direct evidence of collaboration within a professional team or navigating corporate environments.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end solutions, from data preprocessing to model deployment (e.g., serializing models with Pickle for web integration). The focus on reproducible ML and interactive dashboards suggests an understanding of operationalizing data science outputs. However, without direct work experience or psychometric test results, it's difficult to assess soft skills like teamwork, communication in a professional setting, or stress handling.