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Data Science with less than a year in ML pipelines & forecasting.
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Results-driven Data Scientist with hands-on experience deploying end-to-end ML pipelines in production for business forecasting, risk analysis, and customer segmentation. Specializes in classification and regression modelling using Python, Scikit-learn, and XGBoost, with a track record of improving prediction accuracy by 20-25% and boosting minority-class recall by 30% through advanced techniques such as SMOTE and hyperparameter tuning. Proficient in ETL design, Power BI/Tableau dashboards, and cloud platforms (AWS, Snowflake). Actively building skills in MLOps, NLP, and LLM-based applications.
Christian College of Engineering and Technology
B.E. · Computer Science and Engineering
August 1, 2021 – June 30, 2025
Rubixe Al
Data Scientist
July 1, 2025 – January 1, 2026
Bengaluru, Karnataka, India
Skin Disease Multi-Class Prediction
June 1, 2026 – Present
Built a classification model to identify 7 skin disease categories from clinical and histopathological features, achieving 98.65% accuracy using a tuned Random Forest classifier. Performed thorough EDA, handled class imbalance with SMOTE, and used ROC-AUC and F1-score for model evaluation and selection.
View ProjectFIFA-20 Player Clustering & Analysis
June 1, 2026 – Present
Conducted EDA on 18K+ player records to surface age, rating, position, and nationality trends using correlation analysis and visualization. Applied K-Means clustering (k=5 via silhouette analysis) to segment players into actionable performance tiers for scouting use cases.
View ProjectCOVID-19 Cases Time-Series Forecasting
June 1, 2026 – Present
Built ARIMA and Prophet forecasting models on Johns Hopkins COVID-19 dataset to predict confirmed cases and deaths across a 30-day horizon. Benchmarked models using RMSE and MAE; generated insights used to simulate healthcare resource planning scenarios.
View ProjectTexas Employees Salary Prediction
June 1, 2026 – Present
Developed a Random Forest regression model to predict employee salaries, achieving an R² of 0.93 on holdout test data. Applied feature importance analysis to identify top predictors and improve model interpretability for HR stakeholders.
View ProjectSentiment Analysis on Product Reviews
June 1, 2026 – Present
Built an NLP pipeline using TF-IDF vectorization and a Logistic Regression classifier to classify Amazon product reviews as Positive / Negative, achieving 89% accuracy. Explored LSTM-based deep learning baseline as a comparison; applied text preprocessing (stopword removal, lemmatization) with NLTK and spaCy.
View ProjectCertified Data Scientist
Datamites Global Training Institute
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects cover diverse domains (skin disease, sports, public health, HR, e-commerce reviews), indicating a broad interest and adaptability. The professional experience at Rubixe AI aligns well with a Data Scientist role, demonstrating practical application of skills. The breadth of technologies and methodologies used suggests a willingness to learn and apply various tools, which is positive for cultural fit in a dynamic environment. However, the experience is limited to a single role and academic projects, which might indicate a need for more exposure to diverse team structures and corporate cultures.
Soft Skills & Operational Fit
The candidate's resume indicates collaboration with business and product teams, translating analytical findings into actionable strategies, and presenting results to non-technical audiences, suggesting good communication and teamwork skills. The project diversity also implies adaptability and problem-solving capabilities. However, without specific assessment data, these are inferred from descriptions.