Data Analyst at Target
Passionate and dedicated Master of Science in Data Science student at CHRIST (Deemed to be University), Lavasa Campus (2023–2025), with a strong foundation in Statistics (B.Sc., Patna Science College). My professional journey at Target Corporation, Bengaluru, began as a Data Analyst Apprentice and continued as a Business Intelligence Analyst, where I gained hands-on experience in data analysis, automation, visualization, and machine learning.
At Target, I developed dynamic dashboards with drill-down features, resolved large-scale data discrepancies, automated API data extraction and reporting for sustainability metrics (Zero Waste Tracker), and delivered insights into pest control demand trends across stores. I also built ML models with 94% accuracy, optimized categorization using GridSearchCV, and improved data match rates to 99.1%. My role involved close stakeholder collaboration, ensuring data accuracy, and presenting insights that directly supported decision-making.
Beyond corporate projects, I have developed impactful academic and hackathon solutions, such as a Potato and Tomato Plant Disease Detection system using TensorFlow and Django, a Credit Risk Management System leveraging ML models like Decision Trees and XGBoost, and a Food Recipe Website with full CRUD functionality. I also contributed to the Let Us Dream Triennial International Conference 2023 at Christ University by analyzing live feedback data to drive community insights.
My technical expertise spans Python, SQL, TensorFlow, Django, R, APIs, and Power Apps, with skills in Machine Learning, Deep Learning, NLP, Time Series Analysis, Data Structures & Algorithms, and Project Management. I am adaptable, analytical, and passionate about solving problems at the intersection of data and real-world challenges.
I am open to internship opportunities, research collaborations, and industry networking. Feel free to connect with me to explore how we can leverage data for meaningful insights and positive outcomes.
Skills
Experience
Education
Expertise in Python programming for data analysis, machine learning, and web development. Skilled in using libraries such as Pandas, NumPy, and Scikit-learn to develop efficient and scalable solutions. Accomplished in solving 380+ LeetCode problems, showcasing strong problem-solving skills and algorithmic expertise. Proficient in building and deploying machine learning models, including Convolutional Neural Networks (CNNs) for image recognition and processing. Additionally, experienced in utilizing Natural Language Processing (NLP) techniques for text analysis, sentiment analysis, and language modeling.
Proficient in applying machine learning techniques, including Support Vector Machines (SVM), Decision Trees, and Neural Networks (NN) for predictive modeling and data-driven insights. Specialized in Convolutional Neural Networks (CNNs) for image classification and object detection, as well as NLP for text analysis and language translation. Experienced in data preprocessing, feature engineering, model development, and evaluation, ensuring optimal performance and scalability of solutions.
Experienced in developing dynamic and interactive web applications using Django framework. Skilled in implementing user authentication, CRUD operations, and ensuring seamless user interaction.
Working with Quantum Machine Learning and Big Data, utilizing cloud platforms for processing large-scale datasets and running advanced quantum machine learning models efficiently.
This project focuses on identifying diseases in potato and tomato plants using image processing and machine learning techniques. The model leverages CNN for disease classification, providing accurate predictions for early-stage disease detection in crops.
Conducted in-depth dataset analysis and developed predictive models using Pandas, NumPy, and Python. This project optimized relationships for effective decision-making through data analysis.
Developed a fully functional website using Django, implementing user authentication and CRUD operations to ensure seamless user interaction.
Applied statistical methods to environmental projects, organizing workshops to foster peer learning and providing sustainability insights through data-driven analysis.
Created a platform using Django where users can register and log in. The system provides loan predictions to determine eligibility, gold price predictions, and credit risk management using models like Decision Tree, Linear Regression, and XGBoost.
Thank you