Tidy Finance
An open-source approach to empirical finance in R and Python, with two published textbooks and code that connects raw data to research results.
Explore Tidy FinanceCan your team reproduce its own results?
I examine your workflow end to end, from raw data to final results — then tell you where it's fragile, which risks matter most, and what to fix first.
Discuss your workflow
The Workflow Audit
Find the weak points before they become expensive. You get a clear account of what holds up, what fails, and what your team should fix first.
What I examine
- Data sources and the path to each output
- Code, dependencies, and environments
- Validation, documentation, and manual steps
What you receive
- A prioritized risk register
- A concrete remediation roadmap
- A findings session with your team
Selected clients
I've advised fintechs, start-ups, universities, and regulators on reproducibility and AI.
A three-question self-check
Here's where to start
I can analyse your workflow, code, and documentation to identify what needs attention.
Your email app will open with these questions and your answers ready to review and send.
About me
I'm Christoph Scheuch, a financial economist and former product and data science leader. As Data Editor at the Review of Financial Studies, I verify whether empirical finance research can be reproduced from its data and code. I bring the same independent scrutiny to your team's workflows.
Before consulting, I led product and data science teams at wikifolio. I also co-created Tidy Finance and EconDataverse, open-source resources for reproducible financial and economic research. My work combines checking results with building the systems that produce them.
Open-source work
EconDataverse
R and Python packages that provide consistent access to economic data, helping researchers build transparent, repeatable workflows.
Explore EconDataverseLet's discuss your workflow
Tell me where your team gets stuck. I usually reply within two working days.
Email me about your workflow