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APL and array-programming developer for quantitative finance
Service description
I am an array-language specialist, and APL is my primary tool rather than a curiosity on the side. Where most developers reach for loops and heavy frameworks, I express the same computation as a few dense lines of array operations that run over whole vectors and matrices at once. This is a genuinely different way of thinking about code, and after years of working in Dyalog APL I use it to turn tangled numerical problems into short, readable expressions that map directly onto the mathematics behind them. If you have a pricing model, a risk calculation or an analytics pipeline that feels heavier than it should be, I can usually collapse it into something far more compact and far easier to reason about.
Most of my work sits at the intersection of finance and numerical computing. I build and tune models for option pricing, portfolio and risk metrics, time-series analytics and Monte Carlo style simulation, and I care about both correctness and speed. Because APL treats arrays as first-class values, I can prototype a quantitative idea quickly, validate it against real data, and then keep the very same expressions in production without a rewrite. I am comfortable connecting APL to databases, CSV and market feeds, and packaging results so that analysts and non-APL colleagues can consume them through familiar tools and reports.
A large part of what I do is rescue and maintenance work. Legacy APL systems built decades ago still run critical calculations in banks, insurers and research desks, and the people who wrote them have often moved on. I read that code fluently, document what it actually does, fix the parts that have quietly drifted, and modernize it carefully so it keeps producing the right numbers. Whether you need a fresh model written from scratch, an existing one made faster, or an old workspace brought back under control, I can help.
— APL and Dyalog development for finance and analytics
— Option pricing, portfolio and risk models
— Time-series analysis and Monte Carlo simulation
— Vectorized numerical and mathematical code
— Legacy APL rescue, documentation and modernization
— Data integration with databases, CSV and market feeds
Most of my work sits at the intersection of finance and numerical computing. I build and tune models for option pricing, portfolio and risk metrics, time-series analytics and Monte Carlo style simulation, and I care about both correctness and speed. Because APL treats arrays as first-class values, I can prototype a quantitative idea quickly, validate it against real data, and then keep the very same expressions in production without a rewrite. I am comfortable connecting APL to databases, CSV and market feeds, and packaging results so that analysts and non-APL colleagues can consume them through familiar tools and reports.
A large part of what I do is rescue and maintenance work. Legacy APL systems built decades ago still run critical calculations in banks, insurers and research desks, and the people who wrote them have often moved on. I read that code fluently, document what it actually does, fix the parts that have quietly drifted, and modernize it carefully so it keeps producing the right numbers. Whether you need a fresh model written from scratch, an existing one made faster, or an old workspace brought back under control, I can help.
— APL and Dyalog development for finance and analytics
— Option pricing, portfolio and risk models
— Time-series analysis and Monte Carlo simulation
— Vectorized numerical and mathematical code
— Legacy APL rescue, documentation and modernization
— Data integration with databases, CSV and market feeds
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