Senior Applied Scientist, Supply

About this role

Senior Applied Scientist 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 senior role on an established Supply Data Science team, focused on marketplace dynamics—in particular driving participant supply, demand, and quality through advanced optimization techniques and recommendation algorithm expertise.

You will work closely with existing specialists in this space to design, validate, and scale high-impact algorithmic systems that optimize study matching and participant experience. As a senior scientist, you will lead complex technical directions and help define the right problems to solve, driving both strategy and implementation. 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 mathematical optimization and recommendation algorithms applied to large-scale matching or marketplace problems. Judgement about when to reach for simple statistics, classical ML, LLMs, or agentic approaches. 5+ years applying ML, AI research, optimization, or recommendation systems to complex production 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.