I've worked with scientific data and built the systems behind it

For over a decade, I've worked across scientific data management, software engineering and operational delivery, often wearing several hats at once.

I've worked directly with messy datasets, designed and built complex software systems and managed critical operational services.

Getting my hands dirty with real-world data

I've spent years working directly with messy, complex scientific datasets across physical, chemical, biological and other scientific disciplines.

Quality controlling measurements, recording metadata, documenting datasets and chasing down missing information. Asking scientists about mysterious column headings, missing units, sampling locations and methods — and working out why two spreadsheets supposedly containing the same data told different stories.

That experience taught me that understanding data means understanding where it came from, what it represents, how reliable it is and what might be missing.

It's a foundation I still bring to every data problem I tackle.

Designing and building complex systems

I've personally designed relational databases and developed automated software for data ingestion, decoding, quality control, storage and delivery.

I've extended large, complex legacy systems to accommodate new technologies while protecting existing operations. I've also designed reusable, configuration-driven solutions that replaced repeated bespoke development.

From understanding requirements and designing the architecture through to writing code, testing and controlled production releases, I've done the hands-on engineering.

Keeping critical systems running

I've been responsible for near-real-time operational systems supporting international weather forecasting and climate research.

One of those systems worked towards an international target of delivering decoded, processed, quality-controlled and fully documented scientific data within 18 hours of an ocean float transmitting its measurements.

That responsibility involved understanding complex dependencies between software, databases and data files, managing production changes, introducing safer development and release practices, and building monitoring and diagnostic tools.

I've also led major incident response and data recovery.

I understand the responsibility that comes with keeping important systems working.

AI and machine learning are newer additions to my toolkit.

But my judgment in how I use them comes from more than a decade of living and breathing data, from untangling messy datasets to designing software and keeping complex operational systems running.