Machine Learning, Big Data analytics, Python, Data Analyst, SQL

PRANITA KHOLLAM

Pune, India 888-***-**** **************@*****.*** LinkedIn

PROFESSIONAL SUMMARY

Emerging Data Analyst with expertise in Big Data Technologies, Machine Learning, and programming languages such as Python, R, and Java. Holds a postgraduate diploma in Big Data and Analytics from CDAC Pune and a Master of Computer Applications with distinction. Adept at leveraging advanced data processing and analytics tools to derive insights. Highly proficient in English, Hindi, and Marathi, demonstrating strong communication skills to support cross-functional collaboration SKILLS

Python MySQL Big Data Technologies

Machine Learning R Java

EDUCATION

PG - DBDA (Big Data & Analytics) Percentage: 59.68 Centre for Development of Advance Computing(CDAC) Pune Feb 2025 - Aug 2025 MCA Percentage: 75.82

Pratibha Institute of Business Management Pune Jan 2021 - Oct 2022 BCA Percentage: 67.66

Pratibha College of Commerce and Computer Studies Pune Jan 2020 HSC Percentage: 69.53

Prerana Camp Education Society May 2017

SSC Percentage: 78.6

Kanya Vidyalaya Dehu Pune May 2015

PROJECTS

Taxi Fare Forecasting Using Machine Learning and Big Data Jul 2025 https://github.com/Reetu-Mishra/Taxi_Fare_Prediction This project focused on predicting taxi fares using the NYC yellow taxi trip dataset from Kaggle. We utilized big data technologies such as Hadoop and Spark to manage and process large volumes of trip data. The data was stored in HDFS and processed using PySpark for cleaning, transformation, and feature engineering. Exploratory Data Analysis (EDA) was conducted using Python to identify patterns, trends, and outliers. We used SQL-based queries on large, structured datasets. After preparing the data, we built and compared several machine learning models like Gradient Boosting Regression, XGBoost, CatBoost, and LightGBM to predict fares. We also built dashboards in Tableau and Streamlit for an interactive GUI to show fare trends, predictions, and location-based patterns in a visual way. Employee Leave Management Sep 2022

An Employee Leave Management System is a comprehensive web application designed to automate and simplify the process of handling employee leave requests and approvals. Built with PHP for robust backend logic, it securely manages data in a MySQL database, including employee details, leave types, policies, and request statuses. The user interface is crafted using HTML for structure and CSS for aesthetic styling, ensuring a clear and intuitive experience. JavaScript provides dynamic interactivity on the client side, enabling real-time form validation, dynamic content updates, and asynchronous communication with seamless operations like submitting leave requests or viewing updated balances without page reloads. LANGUAGES

English Hindi Marathi

HOBBIES

Reading, Rock Painting, Singing

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