Applied Scientist / Research Economist

Hushcrasher brings causal inference to decision-making in the video game industry. We do applied research to tackle this industry's hardest problems: revenue forecasting, optimal pricing, figuring out what actually drives a game’s success.

We measure the video game market, predict its outcomes, and optimize its key decisions. Our ambition is to solve its hardest problems: revenue forecasting, optimal pricing, causal factors of success. We turn business questions into optimization problems, helping studios, publishers, and investors make better decisions.

We are looking for someone to lead our machine learning and data science work and to help us build the company's scientific core. You design the models at the heart of our products (forecasting, demand estimation, game similarity through embeddings), help decide which ones we build next, and take them all the way to production. Part of your time goes to research you initiate yourself, with the goal of gaining a better understanding of the video game market. We work as peers: you own your projects.

Questions you might work on:

• What makes two games similar, and how can we better leverage images and other non-textual data to do so?
• What are the best early signals to predict a game’s success, and how precise could we be?
• At what price should a game launch to maximize its revenue, and how should that price vary across time and markets?
• When should a game be released, and how much does the competition matter?
• How much does it cost to make a game? How likely is it to overrun its initial budget?
• Which small design tweaks would causally raise a game’s odds of success?
• How can we detect emerging trends, and declining ones?

Hushcrasher started from the urge to take a subject as far as it can go. We are looking for people who have done the same, whatever the topic: research you led, a model you took to production, a company you founded, a tool people actually use.

You're an economist who thrives in a tech environment, juggling machine learning and causal inference from observational data. A research background is a plus. You are versatile, as comfortable with theory as with shipping, and at ease in a young company. You treat your work as a craft and hold a high bar.

Hushcrasher was founded in January 2026 by a PhD economist, and a former VC advisor turned game studio manager. Since then, the company secured €800k in grants, put our first models into production, launched a newsletter read by 1,300 industry professionals, and started building a demand model with an economist at ZEW and advice from a PhD candidate at Harvard. We work fully remote within the EU, with a few in-person meetups in Paris during the year. We offer equity and sponsor French work permits for candidates based outside the EU.

If that sounds like you, we should talk.