Reproducible by design
Tidy
I help banks, asset managers, and research teams build quantitative work that any auditor, regulator, or referee can reproduce straight from the raw data.
From black box to trustworthy
I help finance and economics teams build reproducible and auditable workflows — so analysts spend their time generating insight, not defending it.
I've advised fintechs, universities, and regulators on reproducibility and AI.
How reproducible is your team's work?
A 60-second self-check to find where my help would make the biggest difference.
How confident are you that your team's analyses can be fully reproduced from raw data?
What's your biggest concern about AI and ML in your workflows?
Where would outside help have the biggest impact?
Let's talk
Based on your responses, I'd love to explore where I can help. A 30-minute discovery call, no commitment.
About me
I'm Christoph Scheuch — a financial economist who believes trustworthy data and AI have become a business necessity, not a research luxury. I co-created Tidy Finance and EconDataverse, two open resources for reproducible research in economics and finance, and I research and teach at HU Berlin. As Data Editor at the Review of Financial Studies, a leading journal in financial economics, I'm responsible for verifying that published research can be reproduced from its data and code.
I'm not a pure academic, though. Before my current research role I spent two years as an independent consultant, and earlier led product and data science teams. So I know what it takes to make reproducibility work inside a real organization, not just advocate for it.
I work with the tools your team already uses — and only recommend changes when they meaningfully improve reproducibility, auditability, or speed.
I split my time between Berlin and Vienna, working with clients worldwide.
Contact me
Tell me what you're working on — I'll get back to you within a couple of days.
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