Data Analyst with 1+ years in Machine Learning & Statistical Modeling
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Results-driven Data Analyst and Statistician with expertise in Machine Learning, Statistical Modeling, and Big Data technologies. M.Sc. Statistics graduate (University of Kerala) with hands-on experience in Python, R, SQL, and Spark. Proven ability to design predictive models achieving R² = 0.9935 and 100% classification accuracy. Adept at transforming complex datasets into actionable insights for decision-making across agricultural, healthcare, and business domains. Seeking roles in Data Analytics, Data Science, Biostatistics, or Business Intelligence.
University of Kerala
Master of Science (M.Sc.) · Statistics
August 1, 2024 – June 30, 2026
Sri C Achuthamenon Govt. College, Thrissur
Bachelor of Science (B.Sc.) · Statistics
N/A – June 30, 2024
State Agricultural Price Board
Data Analyst Intern
August 1, 2025 – Present
Kerala, India
Luminar Technolab
Data Science Intern
July 1, 2022 – February 1, 2023
Kerala, India
Statistical Study of World Cocoa Production and Price
August 1, 2025 – September 1, 2025
Analyzed 30+ years of global cocoa production and price data (1994-2025) using national and international data sources. Applied descriptive statistics, CAGR, CDVI, and time series forecasting to examine productivity trends and price volatility. Identified strong domestic vs. international price correlations (r ≈ 0.90) and seasonal price indices, supporting export strategy recommendations.
Predicting Crop Yields Using Agricultural Data
January 1, 2025 – July 1, 2025
Analyzed 19,000+ agricultural records (1997–2020) incorporating rainfall, fertilizer use, pesticide usage, and cultivated area as input features. Built and compared Linear Regression, Decision Tree, and Random Forest Regressors; achieved R2 = 0.9135 with Random Forest a near-perfect predictive model. Delivered yield prediction insights that can support government and agribusiness planning and resource allocation.
Heart Attack Risk Prediction using Machine Learning
July 1, 2024 – August 1, 2024
Analyzed 1,300+ patient health records to identify key cardiovascular risk factors using Logistic Regression, Decision Tree, and Random Forest. Achieved 90% classification accuracy with Decision Tree and Random Forest, validated through F1-score, precision-recall, and confusion matrix analysis. Demonstrated applicability to biostatistics and clinical risk stratification in healthcare settings.
Big Data Analytics & Data Science
NACTET
January 1, 2023 – Present
Workshop on Statistical Analysis Using SPSS
IBM India Software Labs
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's academic background in Statistics, coupled with internships in Data Analyst and Data Science roles, indicates a strong alignment with analytical and data-driven cultures. The diversity of projects (agriculture, finance, healthcare) suggests adaptability and a broad interest in applying data skills across different domains. Their continuous learning through certifications also points to a proactive and growth-oriented mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills through their project work and internship experiences. Their ability to collaborate in cross-functional teams and communicate findings suggests good operational fit. The academic projects show initiative and a structured approach to data analysis.