Data Analyst with less than a year in data analysis and visualization.
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Aspiring Data Analyst Intern with a strong academic foundation in data analysis and statistics, and hands-on experience using SQL, Python, and Excel for data cleaning, data manipulation, and exploratory data analysis. Proficient in creating meaningful data visualizations using Power BI / Tableau to support data-driven decision-making. Detail-oriented with strong problem-solving and analytical skills, eager to apply theoretical knowledge to real-world business datasets, learn industry best practices, and contribute effectively to organizational goals.
Dr. A.P.J. Abdul Kalam Technical University (AKTU)
Bachelor of Technology · Computer Science & Engineering
August 1, 2023 – June 30, 2027
OLA Ride Data Analysis Dashboard
January 1, 2023 – June 1, 2026
Analyzed OLA ride data using SQL to extract insights on trip patterns, peak hours, and revenue metrics. Cleaned and transformed raw ride datasets to prepare for meaningful analysis. Created interactive Power BI dashboards to visualize key ride trends and performance indicators. Used data visualization to support data-driven decision insights and highlight patterns in ride behavior.
View ProjectCustomer Trends Analysis
January 1, 2023 – June 1, 2026
Analyzed customer purchase data using Python and SQL to identify buying patterns and trends. Performed data cleaning and preprocessing to handle missing and inconsistent data. Conducted Exploratory Data Analysis (EDA) to understand customer behavior and key metrics. Used SQL queries to extract insights related to customer segments and purchasing frequency. Created interactive dashboards in Power BI to visualize trends and support data-driven decisions. Summarized insights in a clear and structured format for easy understanding by stakeholders.
View ProjectTrader Performance vs Market Sentiment
January 1, 2023 – June 1, 2026
Analyzed the relationship between trader performance and Bitcoin market sentiment (Fear / Greed) using real trading and sentiment data. Performed data cleaning, preprocessing, and feature engineering to prepare datasets for analysis. Explored key metrics such as daily profit/loss (PnL), win rate, trade frequency, and leverage to understand behavior patterns under different sentiment conditions. Used Python data analysis tools and visualizations to uncover insights and patterns in trader actions during Fear and Greed market phases. Summarized findings and suggested actionable strategies to optimize trading performance based on sentiment trends.
View ProjectCultural Fit Analysis
The candidate's academic projects demonstrate an interest in applying data analysis to real-world scenarios, which aligns with a results-oriented culture. The diversity of projects (customer behavior, financial markets, logistics) suggests adaptability and a broad interest in different data challenges. However, as an aspiring intern with no professional experience, the depth of cultural fit cannot be fully assessed without further interaction.
Soft Skills & Operational Fit
The candidate's profile highlights strong problem-solving and analytical skills, along with a detail-oriented approach. The project descriptions indicate an ability to summarize insights clearly, which is crucial for stakeholder communication. However, without specific assessment data on communication or teamwork, it's difficult to fully assess operational fit beyond self-reported attributes.