Ansila Mol KP
Perinthalmanna,India
Summary
Data professional with expertise in SQL, Python, and Power BI, skilled in exploratory data analysis and business reporting. Demonstrates strong problem-solving abilities and analytical thinking, with a talent for data storytelling and visualisation. Adept at interpreting trends to drive strategic insights. Committed to leveraging data skills to enhance business decision-making processes.
Overview
4
4
years of post-secondary education
Work history
Data analyst Intern
Edunet Foundation
Bangalore, India
10.2023 - 12.2023
- Analyzed real-world datasets using Python (Pandas, NumPy) to perform data cleaning, data preprocessing, and exploratory data analysis (EDA).
- Created data visualizations using Matplotlib and Seaborn to identify trends, patterns, and insights for business reporting.
- Built interactive dashboards and reports in Power BI, enabling stakeholders to track key metrics and make data-driven decisions.
- Applied SQL-ready analytical thinking to structure datasets for reporting and dashboard consumption.
- Gained exposure to Microsoft Azure for managing data workflows, including Azure Data Factory, Azure Storage, and Azure Machine Learning.
- Developed a strong foundation in data analysis techniques, including feature engineering, basic model evaluation, and performance interpretation.
- Documented analysis findings and presented insights in a clear, structured format suitable for non-technical audiences.
Education
Bachelor of Technology - Computer Science and Engineering
Eranad Knowledge City Technical Campus
Kerala 06.2021 - 04.2025
Skills
- SQL
- Python
- Power BI
- Problem Solving
- Exploratory data analysis
- Business reporting
- Data storytelling
- Able to interpret trends
- Analytical thinking
- Data visualization
- Feature engineering
- Data mining techniques
Projects
- Analyzed and processed 5,000+ documents using OCR and Python to extract structured data with 92% accuracy.
- Worked with large labeled datasets (10,000+ records) to classify documents into 5 categories, achieving 80% accuracy and improving data quality by reducing classification errors by 25%.
- Performed data cleaning, validation, and analysis to improve document retrieval efficiency by 30% and reduce processing time from 3.5s to 2.4s per document.
- Created performance metrics and reports to evaluate model results and workflow efficiency, improving overall user productivity by 35%.
Timeline
Data analyst Intern
Edunet Foundation
10.2023 - 12.2023
Bachelor of Technology - Computer Science and Engineering
Eranad Knowledge City Technical Campus
06.2021 - 04.2025