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Junior Data Analyst with 1+ years in data cleaning & visualization
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Assessing your cultural and operational fit
Data Analyst with hands-on experience in data cleaning, preprocessing, visualization, and reporting using Python, SQL, Excel, and Power BI. Skilled in analyzing structured datasets to identify trends, generate actionable insights, and support data-driven decision-making. Proficient in Pandas, NumPy, and dashboard creation with a strong understanding of business analytics and reporting. Experienced in working with machine learning concepts, API integration, and data validation techniques. Strong problem-solving, analytical, and communication skills with the ability to transform raw data into meaningful business insights.
Boston Institute of Analytics, Trivandrum
Diploma · Data Science and AI
August 1, 2024 – June 30, 2025
EKN Model Polytechnic College Kalliasseri, Kannur
Diploma · Computer Hardware Engineering
August 1, 2020 – June 30, 2023
Govt. Higher Secondary School, Thottada
Higher Secondary Education
June 1, 2018 – May 31, 2020
Govt. Higher Secondary School, Thottada
High School Education
June 1, 2015 – May 31, 2018
Ladder7 Nextstep Solutions
Junior Data Scientist Intern
May 19, 2025 – August 14, 2025
Thiruvananthapuram, Kerala, India
First Quadrant Labs
Data Science Intern
April 25, 2025 – June 25, 2025
United Kingdom
Self-Employed
Freelance IT Support Specialist & Graphic Designer
October 10, 2023 – October 10, 2024
India
Customer Churn Analysis & Prediction Dashboard
June 1, 2026 – Present
Analyzed telecom customer datasets using Python, SQL, Pandas, NumPy, and Power BI to identify churn patterns and customer behavior insights. Performed data cleaning, preprocessing, feature engineering, and exploratory data analysis (EDA) on structured datasets. Developed interactive Power BI dashboards for churn trends, customer segmentation, revenue analysis, and KPI tracking. Identified key churn drivers including tenure, monthly charges, payment methods, and contract type using statistical analysis and visualization. Built and evaluated machine learning models including Logistic Regression, Random Forest, SVM, and KNN for customer churn prediction. Achieved 81% prediction accuracy using Logistic Regression and evaluated model performance using ROC-AUC, confusion matrix, precision, recall, and F1-score.
Bitcoin Price Forecasting Using Machine Learning and Time Series Models
June 1, 2026 – Present
Built predictive forecasting models using Gradient Boosting Regressor, ARIMA, and SARIMA on historical Bitcoin price datasets. Performed time-series preprocessing, feature engineering, trend analysis, and hyperparameter optimization. Evaluated forecasting accuracy using regression metrics and time-series validation techniques. Visualized market trends and forecasting insights using Python and Matplotlib. Created a Streamlit-based web application for real-time Bitcoin price forecasting and analytics reporting.
Breast Cancer Risk Prediction using Machine Learning
June 1, 2026 – Present
Developed an end-to-end breast cancer prediction system using Python, Scikit-learn, and Streamlit. Conducted exploratory data analysis (EDA), feature selection, and preprocessing to improve model performance. Applied missing value handling, label encoding, feature scaling, and data transformation techniques. Optimized Random Forest Classifier using GridSearchCV for hyperparameter tuning and improved prediction accuracy. Evaluated models using accuracy, precision, recall, F1-score, and confusion matrix metrics. Deployed the solution as a Streamlit web application with real-time prediction and input validation.
Twitter Sentiment Analysis Using Al
June 1, 2026 – Present
Developed a real-time sentiment analysis application using Hugging Face Transformers and RoBERTa-based NLP models. Preprocessed tweet datasets using text normalization, tokenization, URL cleaning, and mention handling techniques. Generated sentiment classification outputs for Positive, Neutral, and Negative categories using softmax probability scoring. Created analytical sentiment reports and trend insights to support social media and business intelligence analysis. Integrated the NLP model with Streamlit for interactive real-time sentiment visualization.
Doctor Al Chatbot Using LLM
June 1, 2026 – Present
Developed an AI-powered healthcare chatbot using Streamlit and GROQ large language models (LLMs) for real-time medical assistance. Implemented dynamic prompts, API integration, secure API key handling, and configurable system instructions. Designed an interactive sidebar for model selection and personalized chatbot configurations. Added session-state management to maintain conversation history and contextual responses. Demonstrated hands-on experience in LLM deployment, AI application development, and conversational AI systems.
Diploma in Data Science And Al
Boston Institute Of Analytics, Trivandrum
June 1, 2026 – Present
What is Generative Al?
Linkedin Learning
June 1, 2026 – Present
IoT & Robotics Training
Institute of Human Resources Development (IHRD)
June 1, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong interest in data science and AI through diverse personal projects and internships, aligning well with a data-driven culture. The projects cover various domains (telecom, finance, healthcare, social media, real estate), indicating adaptability and a broad learning appetite. The pursuit of a Diploma in Data Science and AI, alongside practical project work, shows initiative and a commitment to continuous learning. The freelance experience, while not directly data-related, suggests independence and client management skills. The target role of 'Junior Data Analyst' is well-aligned with the candidate's demonstrated skills in data analysis, visualization, and basic machine learning, although some projects lean more towards a Junior Data Scientist profile.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving and analytical skills, particularly in identifying churn drivers and optimizing model performance. The freelance IT support role suggests a customer-centric approach and ability to manage multiple tasks. The focus on end-to-end project development, from data preprocessing to deployment, indicates a practical and results-oriented mindset. However, without specific psychometric or English test results, a deeper assessment of work attitude, stress handling, and team collaboration is not possible.