Aspiring Data Scientist focused on analytics, machine learning, and visual storytelling through data. I analyze patterns, build intelligent models, and create polished dashboards that make complex information easier to understand.
I enjoy exploring datasets, uncovering trends, and translating analysis into clear insights, predictive systems, and decision-ready visuals.
Data Science student focused on machine learning, analytics, and meaningful data-driven solutions.
I’m an aspiring data scientist who enjoys working with data from exploration to interpretation. I like cleaning datasets, finding meaningful patterns, and building models that turn raw information into useful outcomes.
My interests are centered around machine learning, exploratory data analysis, and business intelligence. I’m especially drawn to projects where strong analysis, clear visual communication, and practical model performance all matter.
These are the skills I rely on most for cleaning data, finding trends, training models, and presenting insights effectively.
I focus on combining statistical thinking, practical coding, and visual communication to make analysis more useful and actionable.
This section highlights the technologies I use to work with data pipelines, visual reports, experimentation, and project delivery.
These project cards highlight data analysis workflows, machine learning models, and dashboard-driven communication.
An analytics project focused on revenue trends, regional comparisons, and KPI tracking through clear dashboard design and business-facing visual insights.
A supervised learning project that analyzes academic and behavioral variables to predict student outcomes and compare model performance across multiple algorithms.
A data analysis project that investigates customer behavior, visualizes churn patterns, and builds an initial classification model to identify retention risks.
This timeline reflects how I’ve been growing from programming fundamentals into analytics, data storytelling, and machine learning practice.
Built a strong base in programming and problem solving, developing comfort with logic, structured thinking, and Python as a core tool.
Started working with datasets using Pandas, NumPy, Matplotlib, and Seaborn to uncover trends, clean data, and communicate findings visually.
Began building machine learning projects with Scikit-learn, applying feature engineering, model evaluation, and dashboard-driven presentation to real problems.
If you have a project, collaboration, or opportunity in mind, send a message and I’ll get back to you.