also known as Proof Matcher on the internet
Data and pricing analyst. I take messy data and turn it into pricing, revenue and forecasting calls a team can act on, mostly with SQL, Python and Excel. Five worked case studies below. MSc Data Science, Victoria, BC.
View the work →Each one runs from the business question through the analysis and the dashboards to the recommendation, the same way I would hand it over at work.
A pricing model in Python and SQL that weighs demand, competitor ranges, stock, seasonality and conversion, then suggests a price for each product.
MRR, churn, lifetime value and cohort behaviour pulled apart in SQL and Python to see what keeps customers and which revenue is most at risk.
Worked out in Excel and Python how discounts and campaigns moved volume, revenue and margin, and which discount depth was actually worth running.
Demand and revenue modelled in Python from occupancy, lead time, seasonality and price bands, so pricing and capacity calls can be made weeks ahead.
Real numbers from pages I run: Facebook to 572K and Instagram to 387K, tracked in Excel and grown through steady testing.
A two page data & pricing analyst CV that maps to every project here.
Request resumeThe stack I use to move from a raw table to a decision a business can act on.
Every case study is structured the way a hiring team reviews analytical work.
I'm a data analyst based in Victoria, BC. I have an MSc in Big Data and Data Science and a BSc in Computer Science, and I've spent the last few years on dashboards, data pipelines and forecasting, plus my own digital products where I lean on the numbers to grow them.
Most days I am in SQL pulling and shaping data, in Python cleaning and modelling it, and in Excel for quick checks and the odd model a client wants to poke at themselves. The bit I enjoy is the end of it, when a messy table finally turns into something a person can actually decide on. These projects are how I keep that sharp.