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Data with 1+ years in data visualization & Python analytics
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Aspiring Data Analyst with hands-on experience in Python, SQL, Excel, and Power BI. Skilled in data cleaning, preprocessing, exploratory data analysis, and dashboard development. Experienced in using Pandas, NumPy, Matplotlib, Seaborn, SQL, and Power BI to transform raw data into actionable insights. Demonstrated ability to process and clean large datasets, develop compelling visualizations, conduct EDA, and create interactive dashboards.
President institute of computer application,Gujarat University
BCA-Bachelor of Computer Applications · Computer Applications
N/A – June 30, 2026
Vidhya Sabha School
Higher Secondary Education
N/A – May 31, 2023
Chintan Thesiya
January 1, 2025 – June 1, 2026
Practices with lots of data. Processed and cleaned large datasets using Python (Pandas, NumPy) to ensure data integrity. Developed compelling data visualizations leveraging Matplotlib and Seaborn for deeper insights. Conducted exploratory data analysis to identify key trends and patterns. Created interactive dashboards with Power BI to effectively present findings. Engineered a face detection system utilizing Python OpenCV (cv2) for advanced image analysis. Applied image processing techniques to enable real-time detection capabilities.
View ProjectMobiles sales data
January 1, 2025 – March 1, 2026
Data analytics practice. Project Title: Motorola Sales Dashboard – All Month Analytics. Purpose: Developed an interactive dashboard to visualize Motorola's mobile sales performance across India for all months. Enabled stakeholders to analyze sales trends, customer behavior, and payment preferences to facilitate data-driven decision-making.
View ProjectCustomer-Churn-Analysis
January 1, 2025 – March 1, 2026
Lead developer. Telecom Customer Churn - Exploratory Data Analysis (EDA). Conducted EDA on telecom customer churn data to identify critical factors influencing customer retention. Analyzed customer behavior to uncover patterns and insights that inform retention strategies. Utilized technologies including Python, Pandas, NumPy, Matplotlib, Seaborn, and Jupyter Notebook.
View ProjectCultural Fit Analysis
The candidate's projects demonstrate a proactive approach to learning and applying data analysis techniques. The diversity of projects, from churn analysis to sales dashboards and even face detection, suggests a broad interest in data-related challenges. This indicates a potential for adaptability and a willingness to explore different domains, which can be a positive cultural fit for dynamic teams. However, all projects are personal, and there is no information on collaborative work or professional experience.
Soft Skills & Operational Fit
The candidate lists teamwork, problem-solving, communication, and adaptability as soft skills. Project descriptions indicate an ability to work on defined tasks and present findings, which aligns with operational needs for data analysis roles. However, without direct work experience or specific examples, the depth of these soft skills in a professional setting is difficult to fully assess.