MONSE
ROJO
Data Scientist
& Analyst
ABOUT

I'm transitioning from office administration into data science, combining hands-on business experience with technical skills in Python, machine learning, and data visualization.

In my previous role, I handled job costing and budget tracking, analyzing spending across multiple projects and identifying cost patterns. That hands-on work with real business data sparked my interest in data analysis at scale. While finishing my bachelor's degree, I've been building technical projects that demonstrate my growing capabilities in exploratory analysis, predictive modeling, and data storytelling.

Currently developing expertise in: data manipulation (Pandas, NumPy), visualization (Matplotlib, Plotly), machine learning (scikit-learn), web scraping (BeautifulSoup), SQL databases, and natural language processing.

PROJECTS
COMPLETE
Twitter Trends Analysis
Exploratory data analysis of 12,000+ trending hashtags from Twitter/X (2020-2025). Analyzes viral patterns, major world events, and social media engagement metrics using time series analysis and statistical visualization.
Python Pandas Matplotlib Seaborn
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COMING SOON
Interactive Dashboard
Building an interactive analytics dashboard with real-time data visualization capabilities. Demonstrates ability to translate complex data into actionable business insights through dynamic visual interfaces.
Python Plotly Dash Pandas
IN PROGRESS
COMING SOON
Predictive ML Model
Machine learning model for prediction and classification tasks. Features comprehensive data preprocessing, feature engineering, model selection, and performance evaluation using industry-standard metrics.
Scikit-learn XGBoost Python NumPy
IN PROGRESS
COMING SOON
Web Scraping Pipeline
Automated data collection pipeline that scrapes, cleans, and analyzes web data at scale. Demonstrates ETL processes, data quality management, and practical application of web scraping techniques for real-world analysis.
BeautifulSoup Selenium SQL Pandas
IN PROGRESS
COMING SOON
NLP Sentiment Analysis
Natural language processing application for sentiment analysis and text classification. Processes large volumes of text data to extract insights, classify sentiment, and identify patterns in unstructured content.
NLTK TextBlob Python Scikit-learn
IN PROGRESS
COMING SOON
Data Automation Tool
Automated data cleaning and transformation pipeline that processes messy datasets into analysis-ready formats. Demonstrates ETL best practices, error handling, and workflow optimization for repeatable data operations.
Python Pandas NumPy Automation
IN PROGRESS
EXPERIENCE
Data Entry / Administrative Assistant
AYERS CONTRACTING COMPANY INC.
Handled data entry and office administration. Took initiative to build Excel-based tracking systems for job costs and project budgets, analyzing spending patterns across projects and generating reports to flag cost issues. Working with real business data and uncovering patterns is what hooked me on data analysis and pushed me toward data science.
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