Applied Scientist, Supply

Applied Scientist

Team: Supply, Distribution Team

Prolific

You'll join Prolific's Supply team, which is responsible for the health and growth of our participant marketplace, the supply side of our two-sided marketplace connecting participants and researchers. This is a new role on an established Supply Data Science team, focused on marketplace dynamics—in particular understanding and predicting participant supply, demand, and quality, and using that to improve how participants are matched to studies. You will work closely with existing specialists in this space to find, validate, and model useful signals for participant supply and quality and turn promising directions into production systems. The ideal candidate will help define the right problems to solve, not just execute against a fixed brief.

The role

The Applied Scientist role is new to Prolific. It combines data science, ML, and statistics to build practical systems that drive real business outcomes. This isn't a pure research role, although you may explore papers and explore new ideas. The focus is on turning promising approaches into production-ready solutions. It is also not an ML engineering role: you don't need engineering experience, but you should understand what deploying a model involves and the practical constraints around it. We care about approaches that actually work in production, not ones that are too slow or expensive to run, and about the judgement to tell the difference.

What you'll bring

Deep expertise in one applied ML, statistics, or data science specialism.

Examples could be marketplace or supply-demand modelling, pricing and incentive optimisation, or matching and recommendation systems, but any area of genuine depth counts

Judgement about when to reach for simple statistics, classical ML, LLMs, or agentic approaches.

3+ years applying ML, AI research, or data science to real problems.

Python skills sufficient to build, test, and iterate on working prototypes independently.

Able to take a loosely defined product or customer problem and turn it into clear hypotheses, experiments, and metrics.

You must be comfortable working on ambiguous problems and suggesting solutions rather than waiting to be told exactly what to do.

Nice to have

An MSc or PhD in Computer Science, Maths, Statistics, Economics, Psychology, ML, or a related field—or equivalent knowledge gained another way.

Experience working alongside product and engineering teams.