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Data Analyst with less than a year in Data Science & Machine Learning
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Results-driven Data Analyst with 8+ internship experiences spanning Data Science, Machine Learning, Power BI, Business Intelligence, and Healthcare Analytics. Proficient in Python, SQL, Power BI, DAX, Pandas, and Scikit-learn. Demonstrated ability to design predictive models, build interactive dashboards, perform exploratory data analysis, and deliver actionable business insights across domains including HR, Sales, Healthcare, and Customer Analytics. Currently pursuing B.E. in Computer Science & Engineering (CGPA: 8.69) with a strong record of applying data-driven decision-making to real-world problems.
PPG Institute of Technology, Anna University
B.E. · Computer Science & Engineering
August 1, 2023 – June 30, 2027
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Heart Attack Analysis
April 1, 2026 – April 30, 2026
Conducted heart attack risk factor analysis using data analytics and machine learning techniques on clinical datasets. Performed exploratory data analysis and generated comprehensive analytical reports on cardiovascular risk indicators. Applied Python visualization libraries (Matplotlib, Seaborn) for predictive insights and stakeholder-ready reporting.
MediSight Early Disease Analyst System
March 1, 2026 – March 31, 2026
Built a disease prediction and early-warning analysis system using Python machine learning models and Streamlit. Performed data preprocessing, EDA, and visualization on healthcare datasets to identify disease risk factors. Developed an interactive web application delivering early disease insights for medical decision support
Product Sales Dashboard
November 20, 2025 – December 20, 2025
Developed interactive Power BI dashboards for product sales analysis tracking revenue, volume, and regional performance. Created visual reports to monitor sales KPIs, trends, and year-over-year comparisons for business stakeholders. Improved data visualization and reporting efficiency using Power BI best practices and DAX calculations
Customer Churn Prediction Dashboard
August 1, 2025 – October 31, 2025
Delivered a full analytics pipeline from raw data ingestion to visual reporting over a 3-month engagement. Performed EDA, data cleaning, and statistical analysis on customer behavior datasets to uncover churn risk patterns. Built an interactive churn analytics dashboard helping business teams identify at-risk customers and reduce revenue loss.
Human Resources Dashboard
June 1, 2025 – July 31, 2025
Cleaned and analyzed HR datasets to identify workforce trends, attrition patterns, and key performance indicators. Designed an interactive Power BI dashboard visualizing headcount, department distribution, and employee turnover metrics. Communicated findings through data storytelling to support evidence-based HR management decisions.
Churn Prediction
February 1, 2025 – February 28, 2025
Developed a customer churn prediction model using Python and Scikit-learn classification algorithms with Streamlit deployment. Performed end-to-end data preprocessing: missing value treatment, feature encoding, scaling, and model evaluation. Evaluated model performance using accuracy, precision, recall, and ROC-AUC metrics to optimize predictions
Turf Booking System Website
August 1, 2024 – August 31, 2024
Completed hands-on full-stack web development training; designed and built a responsive turf booking web application.
Rising Star Research Academy
Celonis
June 1, 2026 – Present
Data Analytics Job Simulation
Deloitte
June 1, 2026 – Present
Data Analytics Certification
Unstop
June 1, 2026 – Present
Google Analytics Certification
June 1, 2026 – Present
Claude Code in Action
Anthropic
June 1, 2026 – Present
Building Data Analyst AI Agent
Analytics Vidhya
June 1, 2026 – Present
Rising Star Business Academy
Celonis
June 1, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong interest in data analytics and machine learning, aligning well with a data-driven culture. The diversity of academic projects (healthcare, sales, HR, customer churn) shows adaptability and a broad interest in applying data science to different business problems. The numerous internships, though short-term, indicate a proactive approach to gaining experience. However, the lack of professional, long-term experience means cultural fit for a senior role would need to be assessed further during interviews, particularly regarding collaboration within established teams and navigating complex organizational structures.
Soft Skills & Operational Fit
The candidate lists analytical thinking, problem-solving, data storytelling, communication, quick learning, and team collaboration as soft skills. The project descriptions indicate practical application of analytical thinking and data storytelling. Given the academic nature of projects and internships, the operational fit for a senior role would require further validation of these soft skills in a professional, high-pressure environment.