Hi, I'm Christoph Scheuch.

I'm a financial economist and former product and data science leader. I help teams see how their research workflows actually run: where they may break, and what to fix first.

As Data Editor at the Review of Financial Studies, I verify that empirical finance research can be reproduced from its data and code. Previously, I led product and data science teams at wikifolio. That experience shapes how I work: examine the evidence, understand the constraints, and make the next steps practical.

Discuss your workflow View my CV

How I work

We start by analysing your workflow, using the code and documentation your team can share. This first step does not require access to the underlying data.

Map the workflow

I walk through how inputs become outputs with your team, using the available code, documentation, and explanations of each step.

Find the gaps

I examine dependencies, environments, validation, and manual steps to identify gaps that could make the workflow fragile.

Decide what to fix

I hand you prioritized findings and a concrete plan, and we go through them together.

Working with your team

Build repeatable habits

I teach teams how to structure projects, record dependencies, validate outputs, and collaborate on research. We use real examples so the practices carry over to everyday work.

Keep AI outputs traceable

When AI is part of a workflow, I examine how inputs, model versions, settings, and outputs are recorded, and how the team checks the results before relying on them.

Selected publications

Randomness in Large Language Models: What Researchers Need to Know (and Report)

With Guillaume Coqueret, Joan Llull, Florian Oswald, Christophe Pérignon, and Lars Vilhuber · Working paper

Why LLM outputs vary even with unchanged prompts and settings.

Transparent Factor Construction for Empirical Asset Pricing

With Christoph Frey, Stefan Voigt, and Patrick Weiss · Working paper

Research infrastructure for constructing factors in empirical asset pricing.

Tidy Finance with R

With Stefan Voigt and Patrick Weiss · Chapman & Hall/CRC

A textbook on reproducible empirical finance, connecting financial questions to data and code.

Tidy Finance with Python

With Stefan Voigt, Patrick Weiss, and Christoph Frey · Chapman & Hall/CRC

The Python companion, applying the same transparent approach to empirical research.

Teaching

Foundations for Reproducible Research

Barcelona School of Economics

A summer school on reproducible empirical finance, with hands-on work in Python.

Empirical Research in Finance

Humboldt University of Berlin

A seminar connecting financial theory with real data and generative AI tools.

Reproducible Research Workflows

Vienna Graduate School of Finance

A workshop on reproducibility techniques and collaboration in empirical research.

Open-source work

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 Finance

EconDataverse

R and Python packages that provide consistent access to economic data, helping researchers build transparent, repeatable workflows.

Explore EconDataverse

Let's discuss your workflow

Tell me where your team gets stuck. I usually reply within two working days.

Email me about your workflow