I'm Mackenzie, currently pursuing an MSc in Computing and
Information Technology at the University of St Andrews, where I
also completed an MA (Hons) in Social Anthropology. My
interdisciplinary background allows to me approach data with both
technical precision and human insight.
I specialise in translating complex topics into actionable
insights, communicating information clearly to audiences of
varying expertise, using both qualitative and quantitative methods
to inform decisions. My experience includes advising diverse
audiences on practical solutions, managing and cleaning databases
and designing systems to make information more accessible and
useful.
Technical skills include: Python, MySQL, Excel,
Tableau, Power BI, HTML, CSS, JavaScript, Git.
I'm eager to apply my skills to impactful projects where
data-driven insights can make a meaningful difference.
In this SQL project, I cleaned and modeled a dataset of ~500,000
UK e-commerce transactions from 2009–2011 to explore retail
performance and customer behavior. The workflow included loading
messy transactional data, normalizing it into a relational schema,
and running analyses on sales, repeat customers, and retention.
This project demonstrates my skills in SQL-based ETL, data quality
management, and business analysis for real-world retail scenarios.
In this SQL project, I analyzed crowdfunding patterns on
Kickstarter to uncover factors influencing project success and
failure. I prepared a structured schema, ran exploratory queries,
and identified trends across funding goals, categories, and
outcomes—simulating a real-world analytics workflow. This project
highlights my ability to transform raw data into actionable
insights through relational modeling, exploratory analysis, and
business intelligence techniques.
In this Tableau project, I cleaned and transformed a large dataset
of movies and TV shows into an interactive dashboard that reveals
global viewing trends. The analysis explores patterns by country,
rating, genre, and release year, while enabling users to drill
down into individual titles. This project highlights my ability to
turn raw data into actionable insights through interactive
visualization, trend analysis, and business intelligence
storytelling.
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In this project, I designed a data pipeline that consolidated
multiple CSV datasets into a structured MySQL database and
developed an interactive Tableau dashboard to analyze hotel
performance. The visualization tracks revenue, occupancy, ADR,
discounting, and parking utilization, with trends segmented by
hotel type and year. Users can filter results by country or
property type to uncover patterns in demand and
profitability—supporting data-driven decisions around pricing,
resource allocation, and market strategy. This project
demonstrates my skills in SQL-based ETL, data modeling, and
business intelligence storytelling.