Data Analyst with less than a year in data analysis, statistical modeling & machine learning.
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Assessing your cultural and operational fit
Results-driven Data Analyst with M.Sc. Statistics and hands-on experience in end-to-end data analysis, statistical modeling, machine learning, and dashboard development. Proficient in Python, SQL, Power BI, Tableau, and Advanced Excel. Demonstrated ability to clean and analyze large-scale datasets (7,000-8,800+ records), build predictive models (77%+ accuracy), and deliver actionable business insights. Experienced in healthcare research (ICMR-NIE) and industry analytics. Seeking a data analyst role to drive data-informed decision-making.
Kannur University
M.Sc. Statistics · Statistics
July 1, 2023 – June 1, 2025
Sir Syed College, Taliparamba
B.Sc. Statistics · Statistics
June 1, 2020 – May 1, 2023
G-Tec Computer Education
Data Analyst Trainee
September 1, 2025 – January 1, 2026
Kannur, Kerala, India
ICMR – National Institute of Epidemiology
Research Analyst Intern
February 1, 2025 – May 1, 2025
Chennai, Tamil Nadu, India
Customer Churn Analysis
March 1, 2026 – March 1, 2026
Identified churn risk factors for a telecom company using 7,043 customer records. Wrote SQL queries to extract and segment customer data by contract type, tenure, and payment method; used Python (Pandas, Seaborn) for feature-level churn correlation analysis. Built an interactive Power BI dashboard with 8 churn KPIs (churn rate by segment, tenure cohort, contract type) — enabled retention team to prioritize 1,200+ at-risk customers. Result: Dashboard revealed month-to-month contract customers have 3x higher churn — directly actionable for retention campaigns.
HR Attrition Analysis
December 1, 2025 – December 1, 2025
Analyzed 1,470 employee records from IBM HR dataset to identify attrition patterns across job role, department, age group, and salary level. Built multi-page interactive Power BI HR Analytics dashboard with slicers, KPI cards, and drill-through; identified 4 primary attrition drivers with supporting statistical evidence. Result: Dashboard pinpointed that employees aged 25-34 in Sales with below-median salary have 2.5x higher attrition — actionable for HR retention strategy.
View ProjectLoan Approval Prediction
October 1, 2025 – November 1, 2025
Built a Random Forest classifier on 614 loan records to predict approval status; applied SMOTE to address 60/40 class imbalance, improving minority-class recall by 18%. Handled 50+ missing values using median/mode imputation; performed feature importance analysis identifying credit history, income, and loan amount as top predictors. Result: Final model achieved 77% accuracy and 0.81 AUC-ROC — outperforming logistic regression baseline by 9 percentage points.
Netflix Content EDA
October 1, 2025 – October 1, 2025
Performed exploratory data analysis on 8,807 Netflix titles; cleaned 2,600+ missing values and standardized data across 30+ genres and 80+ countries. Uncovered 69% Movies vs 31% TV Shows split; analyzed content growth trends from 1925-2021 revealing 3x surge in content additions post-2015. Tools: Python (Pandas, Matplotlib, Seaborn) — visualized 12+ charts for genre distribution, rating analysis, and geographic content patterns.
Female Autonomy & Health Insurance Coverage
February 1, 2025 – May 1, 2025
Analyzed NFHS-5 national health survey data; applied logistic regression controlling for income, education, and region. Finding: Higher female autonomy significantly increases likelihood of health insurance coverage (OR = 1.43, p < 0.001) — contributed to ICMR research report.
Diploma in Data Analytics
G-Tec Computer Education
January 1, 2026 – Present
Data Visualization Using Excel
WsCube Tech
January 1, 2025 – Present
Data Analysis Using Python
WsCube Tech
January 1, 2025 – Present
Fundamentals of Data Analysis
LearnQuest
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic background in Statistics and practical experience in data analysis roles align well with a Data Analyst position. The projects demonstrate a diverse application of data analysis skills across different domains (telecom churn, loan prediction, HR attrition, health research, entertainment EDA), indicating adaptability and a broad interest in data-driven problem-solving. The mix of personal, academic, and internship projects shows initiative and a continuous learning mindset. The candidate's skills and project diversity suggest a good cultural fit for a data-centric team that values analytical rigor and practical application.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate technical findings into actionable business insights, suggesting good problem-solving and analytical thinking. Collaboration with a team of epidemiologists shows teamwork capability. The focus on delivering insights that informed business decisions highlights a results-oriented approach. However, direct evidence of communication skills beyond written project descriptions is not available.