Data Science with less than a year in predictive modeling and interactive dashboards.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science and Machine Learning enthusiast with a B.Tech in Electrical and Electronics Engineering from SRM Institute of Science and Technology. Proficient in Python, SQL, Power BI, and machine learning frameworks with hands-on experience building predictive models, interactive dashboards, and data-driven solutions. Seeking to apply analytical expertise and technical skills to deliver impactful, data-informed outcomes in a forward-thinking organization.
S.R.M Institute of Science and Technology
Bachelor of Technology · Electrical & Electronics Engineering (EEE)
January 1, 2016 – January 1, 2020
Netflix Data Analysis
June 18, 2026 – Present
Conducted exploratory data analysis on Netflix datasets to uncover content trends, genre distribution, and audience consumption patterns. Utilized Python libraries for data cleaning, visualization, and statistical analysis on large-scale media data. Generated actionable business insights through visual storytelling and trend-based analytics dashboards.
Retail Sales Dashboard
June 18, 2026 – Present
Created interactive reports and KPI cards using DAX measures to enable data-driven business decision-making. Automated data visualization workflows to improve reporting efficiency and streamline insight generation. Designed drill-through pages and slicers for multi-dimensional retail performance analysis across regions and product categories.
House Price Prediction System
June 18, 2026 – Present
Developed a machine learning model for house price prediction using regression algorithms including Linear Regression and Random Forest. Performed data preprocessing, feature engineering, and exploratory data analysis to improve model accuracy. Evaluated model performance using regression metrics (RMSE, MAE, R²) and visualized residuals for interpretability.
Fake News Classifier
June 18, 2026 – Present
Built a fake news classification model using Natural Language Processing and supervised machine learning techniques. Applied TF-IDF vectorization and Logistic Regression / Naive Bayes classifiers for accurate text prediction. Improved classification performance through text preprocessing, stop-word removal, and feature extraction pipelines.
T20 World Cup Analysis Dashboard
June 18, 2026 – Present
Developed an interactive T20 World Cup analytics dashboard using Power BI and SQL for match, team, and player performance analysis. Designed data models and wrote optimized SQL queries to extract and transform raw cricket data for reporting. Built calculated columns and measures using DAX to enable dynamic filtering and in-depth performance comparison across tournaments.
NPTEL ELITE Certification: Non-Conventional Energy Sources
IIT Madras
June 1, 2026 – Present
Google Data Analytics Professional Certification
Coursera
January 1, 2023 – January 1, 2026
The candidate scored only 12% on this assessment, indicating a very weak grasp of data science and artificial intelligence principles, which are critical for the target role.
Limitations
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in data analysis and machine learning, aligning with the target role of Data Science. The projects are diverse in application (Netflix data, retail sales, house price prediction, fake news classification, T20 World Cup analysis), showing a breadth of interest. However, the lack of professional experience and the focus on personal projects might indicate a need for mentorship and adaptation to a corporate environment. The educational background in Electrical & Electronics Engineering, while technical, is not directly in Computer Science or Data Science, which might require additional foundational learning in specific areas.
Soft Skills & Operational Fit
The psychometric test score of 225/500 suggests potential areas for development in logical reasoning, work attitude, stress handling, and team collaboration. The English test score of 53/100 indicates a need for improvement in communication clarity and professional language usage, which could impact operational effectiveness in a senior role.
A score of 15% suggests significant deficiencies in Python programming, data analysis, and related sub-skills, which are foundational for a Data Science role.
Limitations
The candidate achieved a perfect score of 100%, indicating exceptional expertise in Power BI and related business intelligence concepts.
Strengths