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Data Analyst with 1+ years in Data Analysis & Machine Learning
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Highly skilled Data Analyst with 1.3 years of experience in leveraging statistical analysis, machine learning, and business intelligence tools to drive data-driven insights. Proven ability to optimize operational workflows, identify key performance indicators, and develop predictive models for improved decision-making. Adept at data cleaning, visualization, and advanced analytical techniques to support business growth and efficiency.
National Institute of Electronics & Information Technology
PG Program · Data Analytics and Artificial Intelligence
September 1, 2024 – March 1, 2025
University of Calicut
Master of Science · Statistics
January 1, 2022 – January 1, 2024
Vimala College (Autonomous)
Bachelor of Science · Statistics
January 1, 2019 – January 1, 2022
Interval Learning
Data Analyst
June 1, 2025 – Present
Malappuram, Kerala, India
Infocrita Data Solutions
Data Analyst Intern
March 1, 2025 – April 1, 2025
Thiruvananthapuram, Kerala, India
Maternal Health Risk Prediction using Machine Learning
June 24, 2026 – Present
Developed a classification model to predict maternal health risk levels (high, medium, low) using a dataset of 1000+ records and 6 features. Implemented and evaluated 7 machine learning algorithms including Logistic Regression, KNN, Decision Tree, and Random Forest. Achieved 86% accuracy using Random Forest, outperforming other models in predicting risk levels. Performed model evaluation using confusion matrix, precision, recall, and F1-score to assess performance. Conducted feature importance analysis and identified key factors influencing maternal health risk.
E-Commerce Sales & Customer Analytics (SQL Project)
June 24, 2026 – Present
Analyzed e-commerce sales and customer data using SQL across multiple tables (customers, orders, products, order items). Performed Customer Lifetime Value (CLV) analysis to identify high-spending customers. Analyzed monthly sales trends using SQL window functions to track revenue changes over time. Identified best-selling products and category-wise revenue contribution using aggregations. Conducted customer retention and churn analysis based on order history and inactivity periods. Used advanced SQL techniques including joins, subqueries, CTEs, and window functions for data analysis.
Sales Dashboard Analysis (Power BI Project)
June 24, 2026 – Present
Built an interactive Power BI dashboard to analyze sales performance across multiple dimensions. Analyzed key metrics such as revenue, sales trends, and category performance using structured datasets. Created visualizations including bar charts, line charts, and KPI indicators to track business performance. Identified patterns in sales trends and product categories to support data-driven insights. Used data cleaning and transformation techniques to prepare datasets for accurate analysis.
Cultural Fit Analysis
The candidate's academic background in Statistics, coupled with a PG Program in Data Analytics and AI, demonstrates a strong commitment to the field. The projects undertaken are diverse, covering SQL analytics, machine learning, and BI dashboarding, indicating a broad interest and adaptability. The current and internship roles as a Data Analyst align directly with the target role, suggesting a clear career path and motivation. The breadth of tools and technologies mentioned (Python, SQL, R, Excel, Power BI, Tableau, SPSS, Pandas, NumPy) further supports a versatile and learning-oriented mindset, contributing positively to cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions and work experience highlight an ability to identify operational inefficiencies, analyze funnel stages, and generate insights to improve process efficiency. This indicates a proactive approach to problem-solving and a focus on delivering tangible business value, which aligns well with operational fit for a data analyst role.