Name: Ravi Parmar

Job Role: Data Analyst

Experience: 1 Year +

Address: Dhranagadhra-Gujarat, India

Skills

SQL 90%

PYTHON 90%

Data Visualization 90%

Statistical Analysis 85%

Machine Learning 80%

R 60%

Gen-Ai & Prompt writing 90%

About Me

I am a results-driven experienced Data Analyst with hands-on experience in data analysis, machine learning, AI, and web development. I have developed several impactful projects, including Spam Email Classification using Naive Bayes and NLP, Employee Burnout Prediction using Regression, and an AI-powered UI/UX Issue Detection System using MobileNetV2 and Flask, which classifies application interfaces as Good or Bad UX. I also authored and submitted a research paper on the UI/UX project to the 5th International Conference on Smart Systems: Innovations in Computing (SSIC-2025) at Manipal University Jaipur. These projects, along with my internship experiences at AICTE, Edunet Foundation, PSYLIQ, and Oasis Infobyte, have equipped me with strong skills in SQL, Python, Power BI, Excel, and domain-specific analysis across HR, pharma, and UI/UX fields.

Profile: Data Science & Analytics
Domain: General Data Analysis & Industry Agnostic
Education: B.E in Computer Engineering
Language: English, Hindi, Gujarati
BI Tools: Microsoft Power BI, Tableau
Database Management: SQL ,PostgreSQL
Interest: Traveling, Travel Photography, listening to music, Reading Self help books

Resume

Experienced Data Analyst with strong analytical skills, eager to drive business growth through data-driven insights and continuous learning. Passionate about applying data science principles to solve challenges and contribute effectively to success.

Work Experience

2023-2025

Freelance Data Analyst (Contract-based)

Bliss Web Solution Pvt. Ltd.

Bliss Web Solution Pvt. Ltd. is an Ahmedabad-based IT company offering e-commerce, web design, and mobile app solutions across platforms like Magento and Shopify. Since 2011, it has delivered 1,000+ projects globally with a focus on UI/UX and digital innovation.

From Dec 2023 to Mar 2025, I worked remotely as a Freelance Data Analyst with Bliss Web Solution Pvt. Ltd., a company specializing in web and e-commerce development. My role focused on supporting data-driven decisions for digital products and IT services.
I was responsible for analyzing user behavior, sales trends, and system performance data to optimize web and mobile platforms. I developed dashboards and reports that provided clear, actionable insights for internal teams and clients.
Additionally, I built AI models, performed SQL-based data processing, and contributed to strategy planning by interpreting key metrics that impacted marketing, UX design, and business outcomes.

2023

Web Development & Designing Intern

Oasis Infobyte

OasisInfoByte turns digital dreams into reality, aligning with client goals to deliver exceptional software solutions.

Calculator: Developed a web-based calculator application using HTML, CSS, and JavaScript, featuring a user-friendly interface that mimics a physical calculator and provides instant results for basic arithmetic calculations.
To Do List: Created a To-Do List web application using HTML, CSS, and JavaScript, allowing users to organize and manage daily tasks with dynamic features for inputting, displaying, and managing to-do items within the browser.
Tribute Page: Constructed a Tribute Page dedicated to A.P.J. Abdul Kalam, featuring comprehensive information about his life, achievements, and contributions, along with additional resources for further reading.

2023-2024

Data Analyst Intern

Psyliq

Psyliq, a premier internship specialist, bridges the gap between job seekers and real-world projects, empowering professional skill enhancement.

HR Data Analysis: Delved deep into human resources data to extract meaningful insights and contribute to strategic decision-making. Learned the ropes of workforce analytics and its pivotal role in optimizing organizational performance.
Employee Dataset: Worked on a comprehensive employee dataset, honing my skills in data management and analysis. Leveraged the power of data to understand trends, identify patterns, and derive actionable conclusions for workforce enhancement.
In the realm of pharmaceuticals, I explored the vast landscape of data analysis, gaining valuable insights into industry trends and contributing to data-driven strategies. An enriching experience in a dynamic sector.

2024

AICTE (AI Intern): Transformative Learning with TechSaksham-A joint CSR initiative of Microsoft & SAP

AICTE

Edunet Foundation, founded in 2015, bridges academia and industry by enhancing employability, fostering innovation, and leveraging emerging technologies to build an IR 4.0-ready workforce in India.

Spam emails present a growing challenge by reducing productivity and posing security risks. My project, Spam Email Classification using NLP and Machine Learning, focuses on creating a robust solution to differentiate spam from legitimate emails. By implementing machine learning models and natural language processing techniques, this system enhances email filtering, reduces false positives, and improves email security.
The project involved key steps, including text preprocessing with tokenization, stemming, and lemmatization. Feature extraction was done using TF-IDF, and machine learning models like Naive Bayes and Support Vector Machine were trained and evaluated for accuracy. This approach ensured high performance in classifying emails effectively while minimizing misclassifications.
This project provided valuable hands-on experience with Python, Scikit-learn, and Streamlit, showcasing my ability to apply AI-driven solutions to real-world problems. It strengthened my understanding of NLP and machine learning, reflecting my passion for data science and artificial intelligence applications.

2024

AICTE (AI Intern): Edunet Foundation’s SkillsBuild Program, in collaboration with IBM, provided an Artificial Intelligence internship

AICTE

Edunet Foundation, founded in 2015, bridges academia and industry by enhancing employability, fostering innovation, and leveraging emerging technologies to build an IR 4.0-ready workforce in India.

The Employee Burnout Analysis project aims to identify factors influencing employee burnout, a critical issue affecting productivity and workplace well-being. Using a dataset provided by the Edunet Foundation and IBM SkillsBuild, key variables such as mental fatigue score, resource allocation, and designation were explored to analyze their impact on burnout rates.
The project involved thorough data preprocessing, including handling missing values, encoding categorical data, and scaling features. A Linear Regression model was built, achieving an R² score of 0.92. Visualizations, such as correlation heatmaps and scatter plots, provided insights into trends and relationships affecting burnout.
This project highlights the significance of data-driven solutions to workplace challenges. By predicting burnout and identifying contributing factors, organizations can implement strategies to improve employee well-being. The experience strengthened my skills in data analysis, visualization, and machine learning for real-world applications.

2025

AI Intern

Prasunet Pvt Ltd

Prasunet Pvt. Ltd. is an India-based IT company delivering software, AI, cloud, and cybersecurity solutions to help businesses scale and innovate.

During my internship at Prasunet Pvt. Ltd., I developed an AI-powered Automated UI/UX Testing System that classifies mobile and web app interfaces as “Good UX” or “Bad UX” using computer vision and machine learning.
The system leveraged OpenCV for UI feature extraction and used MobileNetV2 as a pretrained model in TensorFlow to build a lightweight yet accurate classifier. I handled class imbalance, integrated the model into a dark-themed Flask web app, and enabled real-time UX evaluation via screenshot uploads.
This project sharpened my skills in AI/ML, UI/UX analysis, and full-stack development, and contributed to improving design workflows by offering fast, automated feedback for product teams.
I also authored a research paper based on this project and submitted it to The 5th International Conference on Smart Systems: Innovations in Computing (SSIC-2025), organized by Manipal University Jaipur (MUJ), highlighting the system’s methodology, implementation, and real-world impact.

Education

2019-2023

B.E in Computer Engineering

LDRP Institute of Technology and Research

Grade: First class.

2017-2019

Higher Secondary School

Sadhana Vidhyalaya

Grade: Second Class.

Download CV

Projects

Below are my practice and work projects showcasing skills in SQL, Power BI, Python, and Machine Learning.

Analyzing Data from a Digital Music Store with SQL

The project analyzes a music store database using SQL queries to extract meaningful insights for business decisions and customer engagement.

Amazon Kindle Book Sales analysis

The goal of this project is to analyze a dataset containing information about Amazon Kindle books. We aim to gain insights into the dataset's characteristics and visualize key aspects such as book prices and categories.

Power BI HR Analytics Dashboard

Designed a power bi dashboard for HR Analytics for employee Attrition in the Company

Weather Forecasting using spreadsheet

The Weather Forecasting project aims to analyze historical weather data to gain insights and make temperature forecasts using spreadsheet.

Optimizing Agricultural Production analysis

The project focuses on enhancing agricultural productivity by applying data analysis and machine learning techniques. It uses datasets that incorporate various crop characteristics, including soil properties and climatic factors, to provide insights and predictive models for optimizing farming outcomes.

Spam Email Classifier Using NLP & ML

The Spam Email Classification project uses natural language processing and machine learning to detect spam emails. It preprocesses text, extracts features using TF-IDF, and applies algorithms like Naive Bayes and SVM to improve email filtering with high accuracy and real-time scalability.

Employee burnout analysis

The Employee Burnout Analysis project involved analyzing employee data to identify patterns and factors contributing to burnout. It utilized machine learning models to predict burnout risks, aiming to help organizations improve employee well-being and retention.

AI-powered Automated UI/UX Issue-Detection System

Developed an AI-powered system that detects UI/UX issues from app or website screenshots. It uses MobileNetV2 with deep learning and computer vision techniques to classify designs as Good or Bad UX. The system features a Flask web app with real-time upload, prediction, and visualization, helping teams improve design quality efficiently.

I'm Ravi Parmar