Analytical and detail-oriented Data Analyst with 2 years of experience in data collection, automation, and visualization. Skilled in Python, SQL, and data scraping with Selenium. Experienced in transforming raw data into actionable insights using Power BI and Tableau. Adept at predictive analytics and machine learning to drive strategic decisions. Eager to contribute technical skills and data-driven thinking in fast-paced environments.

• Python, SQL, PostgreSQL
• Power BI, Tableau
• Data Scraping (Selenium, BeautifulSoup)
• Machine Learning & Predictive Analytics
• FastAPI, Automation Pipelines
• NumPy, Scikit-Learn, Matplotlib, Seaborn

Junior Data Analyst – Cardwatch POS (Canada) | Jan 2024 – May 2024

• Developed and deployed automated data collection tools using Python and Selenium.
• Conducted data audits and cleaning to enhance data quality.
• Integrated automated pipelines for seamless data ingestion into PostgreSQL databases.

Data Analyst – Seair Info Solutions (India) | Jan 2023 – Dec 2023

• Designed and optimized SQL queries to improve data accuracy and performance.
• Automated data validation and transformation processes using Python.
• Implemented web scraping tools for network data acquisition, reducing manual effort.

Product Analyst – Pinnacleworks Infotech (India) | May 2022 – Dec 2022

• Evaluated and optimized Automated Speech Recognition (ASR) models.
• Created automated benchmarking pipeline improving model accuracy by 55%.
• Integrated FastAPI with Python scripts for API testing and deployment.

Durham College – Canada (2025)

Postgraduate Diploma in Artificial Intelligence

Durham College – Canada (2024)

Postgraduate Diploma in Data Analytics

University of Delhi – India (2019–2022)

Bachelor of Science in Mathematics

Smart Stock Project

• Engineered a rule-based inventory management system using the Experta library to proactively manage stock levels, prevent overstocking and stockouts, and optimize reordering processes.
• Implemented dynamic rules to adjust inventory thresholds based on real-time sales data, improving system responsiveness and adapting to changes in market demand.
• Integrated a sophisticated rule set to handle advanced scenarios, including bulk order fulfillment, minimum order quantity compliance, and cost-effective bulk-discount purchasing.

Description-Based Product Recommendation System

• Built a recommendation engine using Sentence Transformers and APIs to suggest products based on semantic similarity.
• Matched input descriptions to product metadata using semantic similarity.
• Deployed in a user-facing web app for real-time recommendations.

Star Classification Using Machine Learning

• Developed classification models (Random Forest, SVM, Logistic Regression) to categorize stars based on parameters.
• Performed EDA using Matplotlib and Seaborn.
• Achieved over 90% accuracy with optimized hyperparameters.

News Scraping and Stock Analysis

• Scraped financial news using Selenium and BeautifulSoup
• Extracted and matched stock symbols to related industry sectors.
• Pulled 30-day historical data from Yahoo Finance.
• Generated automated buy/wait/sell recommendations with visual trend plots.
• Exported all results including plots, news, and decisions for reporting.

Eye Disease Prediction Web App

• Developed a convolutional neural network (CNN) model using TensorFlow/Keras to detect various eye diseases from fundus images.
• Deployed the model as a web application allowing users to upload images and receive predictions in real time.

ClassifyMail Project

• Built an LLM-powered Email Classifier App that classifies emails based on subject and body input.
• Implemented summarization to condense long emails into key insights.
• Automated draft reply generation with context-aware responses using LLMs.