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Data Analyst with less than a year in Python, SQL & Power BI
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented Engineering graduate with hands-on experience in Python, SQL, data analysis, and visualization tools like Power BI and Streamlit. Gained skills in data cleaning and transformation of large datasets, interactive dashboard development with dynamic filters, statistical analysis of trends and patterns, creation of compelling visualizations using Matplotlib and Seaborn, SQL-based data extraction, and customer segmentation analytics. Quick learner with strong analytical thinking, eager to contribute to data-driven roles in a dynamic tech environment.
Technocrats Institute of Technology, Bhopal
Bachelor of Technology · Civil Engineering
August 1, 2020 – June 30, 2024
Gyan Sagar International School, Sohagpur
Intermediate Education · C.B.S.E
N/A – May 31, 2020
Gyan Sagar International School, Sohagpur
Secondary Education · C.B.S.E
N/A – May 31, 2018
Olympic Analysis
December 1, 2025 – December 31, 2025
Cleaned and transformed an extensive dataset of over 270,000 records spanning 120 years of Olympic history, ensuring data integrity by resolving missing values and removing duplicate entries. Analyzed patterns and trends in athlete participation, country-wise medal tallies, and demographic shifts through statistical summaries and visual exploration, uncovering insights into the evolution of Olympic sports. Developed an interactive Streamlit application with dynamic filters allowing users to explore Olympic data by country, year, and sport categories, enhancing accessibility and engagement with complex historical data. Created rich visualizations with Matplotlib and Seaborn to tell compelling stories behind medal distributions and athlete demographics, supporting data-driven discussions and presentations.
View ProjectCredit Card Financial Dashboard
November 1, 2025 – November 30, 2025
Engineered a comprehensive Power BI dashboard that visualizes credit card performance metrics such as quarterly revenue, transaction volume trends, and customer segment analysis to streamline business monitoring. Leveraged SQL and Python to extract, clean, and analyze transactional data by customer income, age, job type, and card category, identifying key drivers of revenue and potential growth opportunities. Delivered actionable insights highlighting top spending sectors like groceries, fuel, and entertainment, enabling targeted marketing efforts and product customization based on customer behavior analytics. Facilitated data-driven decision-making among leadership through provision of real-time KPIs, drill-down capabilities, and automated report generation, significantly enhancing operational transparency and strategic planning.
View ProjectCertified in SQL (Intermediate)
HackerRank
June 1, 2026 – Present
Certified in Python and Python Libraries
Naresh I Technologies
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects, while academic, demonstrate a proactive approach to learning and applying data analysis skills across different domains (sports history, financial services). The use of various tools and technologies (Pandas, SQL, Power BI, Streamlit, Matplotlib, Seaborn) indicates a breadth of technical interest. The focus on creating interactive dashboards and delivering actionable insights aligns with a results-oriented culture. However, the lack of professional experience means cultural fit in a corporate setting is yet to be fully proven.
Soft Skills & Operational Fit
The candidate highlights analytical thinking, problem-solving, effective communication, collaboration, teamwork, and attention to detail. These soft skills are crucial for a Data Analyst role, indicating a good operational fit for data-driven environments where insights need to be communicated clearly and collaboratively. The project descriptions show an ability to translate complex data into actionable insights, which is a key operational requirement.