Introduction
I take client privacy very seriously and follow the practice that McKinsey & Co. used to follow when I worked there: I don't even disclose the names of my clients, unless they explicitly give me permission to do so.
As a result, the projects I show here are anonymised and reflect what my contribution was, but the source code and details are not disclosed. And of course, I will treat your projects with the same level of confidentiality.
Below is a non-exhaustive list of my recent projects:
Management App to the Cloud
Challenge: Migrate the MS Access management app of a knowledge company to a modern cloud infrastructure
Solution: Built a scalable, performant backend on Quarkus with a stylish, convenient frontend in React, transitioning over 15 years worth of accumulated business processes, VBA code and data in 9 months
Technologies: Quarkus, Java 17, React, Postgres, AWS (EC2, CF, CodeCommit, S3)
Agricultural Markets Simulator
Challenge: Build out and document an economic simulation system for a European University... then move it to a modern web UI
Solution: Reverse engineered the existing code and documented it for publication, then built new functionality for the simulation and the user interface
Technologies: Java + Swing, then Quarkus, React and Plotly
GIS Analytics
Challenge: Rapidly develop custom analytics for a client of a major GIS provider
Solution: Built an Excel-based solution in VBA to query the provider API, cache the data and generate the analytics on-demand
Technologies: Microsoft Excel, Visual Basic for Applications (VBA)
Crypto Market Simulation
Challenge: Provide a true view on trade strategy performance using historic data, instead of widely available "sum of percent gain/loss"
Solution: Built and deployed a toolset to test trading strategies against actual historical market data using configurable capital allocation strategies
Technologies: AWS (EC2, CodeCommit), Python, Flask, Wireguard
Multi-CEX Trading Platform
Challenge: Run any number of trading algorithms in parallel against over thousand trading pairs across several centralised crypto exchanges.
Solution: Built and deployed a distributed, scalable, banking-grade streaming platform with high throughput and low latency from exchange data receipt through decisioning to order placement.
Technologies: AWS (EC2, VPC, CodeCommit), Apache Kafka, Rust, Python, Wireguard
Generative Architecture
Challenge: Create randomised virtual properties within pre-defined rarities for an NFT metaverse
Proof of Concept: Built technology demonstrator in Unity 3D that generated a new landscape-aligned randomised set of properties and props based on the set raritiesTechnologies: Unity 3D, C#
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To discuss tailored projects, please connect on LinkedIn.