I'm a Data Analyst with an MSc background in Data Science, passionate about transforming raw, messy data into insights that people can actually understand and act on.
My work sits at the intersection of data analysis, business intelligence, visualization, and predictive analytics.
I enjoy asking the questions behind the numbers:
What happened? Why did it happen? What does it mean? And what should we do next?
My core analytics toolkit includes Excel, SQL, Power BI, Tableau, and Python, complemented by experience with data science and machine learning tools such as Pandas, NumPy, Scikit-learn, TensorFlow, and Jupyter.
📊 Data Analysis
Clean, transform, explore, and analyze datasets to uncover meaningful patterns.
📈 Business Intelligence
Build interactive dashboards and reports that turn business data into decision-ready information.
🎨 Data Visualization & Storytelling
Translate complex datasets into visual stories that are easy for stakeholders to understand.
🤖 Predictive Analytics
Apply statistical and machine learning techniques to explore patterns and make predictions.
🧩 Data Modeling
Structure data effectively for analysis, reporting, and business intelligence.
Excel: Power Query · Power Pivot · Pivot Tables · Advanced Formulas · Dashboards
Power BI: Power Query · Data Modeling · DAX · Interactive Dashboards · Business Intelligence
SQL: Data Exploration · Joins · CTEs · Subqueries · Window Functions · Aggregations
Tableau: Interactive Visualizations · Dashboards · Data Storytelling
Python: Data Analysis · Automation · Statistical Analysis · Machine Learning
Pandas & NumPy: Data Manipulation · Cleaning · Transformation · Numerical Analysis
Scikit-learn: Machine Learning · Classification · Regression · Model Evaluation
TensorFlow: Deep Learning · Neural Networks · Sequence Modeling
Jupyter: Exploratory Data Analysis · Experiments · Data Science Workflows
Visualization: Matplotlib · Seaborn · Plotly · Tableau · Power BI · Excel
I focus on choosing visualizations based on the question being answered, not simply making dashboards look attractive.
Areas I've worked with include:
Regression Classification Time Series Predictive Analytics
Neural Networks LSTM Model Evaluation Feature Engineering
Power BI · SQL · Data Modeling · Business Intelligence
An executive-level sales analytics project designed to transform transactional data into actionable business insights.
Questions explored:
- Which products generate the most revenue?
- Which stores and regions perform best?
- How are sales changing over time?
- Which product categories require attention?
- What trends can help management make better decisions?
Focus: Business intelligence · Data modeling · Dashboard design · Decision support
SQL · Data Analysis · Business Questions
A deep exploration of the data job market using SQL to investigate roles, salaries, skills, and other factors influencing data-related careers.
Focus: SQL analysis · Data exploration · Business questions · Market insights
Power BI · Excel · Data Visualization
An interactive sales dashboard analyzing product performance, revenue, order patterns, and customer purchasing behavior.
Focus: Sales analytics · KPIs · Dashboard design · Data storytelling
Excel · Data Analysis · Visualization
A complete analytical workflow built in Excel, demonstrating how spreadsheets can be used for data cleaning, analysis, visualization, and dashboard creation.
Focus: Excel analytics · Data visualization · Business reporting
Power BI · Data Visualization · Business Intelligence
An interactive dashboard exploring trends within the data job market and translating large datasets into accessible visual insights.
Focus: Power BI · Interactive dashboards · Data storytelling
Python · Jupyter · TensorFlow · LSTM · XGBoost · Machine Learning
A predictive maintenance project focused on estimating the Remaining Useful Life (RUL) of industrial equipment using the NASA C-MAPSS dataset.
The project combines LSTM and XGBoost to improve predictive performance and provide a practical approach to equipment failure prediction.
Focus: Predictive analytics · Deep learning · Machine learning · Time-series data
I don't believe data analysis starts with a dashboard.
It starts with a question.
BUSINESS PROBLEM
↓
UNDERSTAND THE DATA
↓
CLEAN & TRANSFORM
↓
EXPLORE & ANALYZE
↓
IDENTIFY PATTERNS
↓
VISUALIZE INSIGHTS
↓
COMMUNICATE FINDINGS
↓
RECOMMEND ACTION