<h1 style="text-align: center;"><span style="font-family: tahoma, arial, helvetica, sans-serif; color: rgb(126, 140, 141);">Senior Applied Scientist</span></h1> <p style="text-align: center;"> </p> <p style="text-align: center;"><span style="color: rgb(126, 140, 141); font-family: tahoma, arial, helvetica, sans-serif;"><em>Prolific</em></span></p> <p><span style="font-family: tahoma, arial, helvetica, sans-serif;">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.</span></p> <p> </p> <p style="text-align: center;"><span style="color: rgb(126, 140, 141); font-family: tahoma, arial, helvetica, sans-serif;"><em>The role</em></span></p> <p><span style="font-family: tahoma, arial, helvetica, sans-serif;">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.</span></p> <p> </p> <p style="text-align: center;"><span style="color: rgb(126, 140, 141); font-family: tahoma, arial, helvetica, sans-serif;"><em>What you'll bring</em></span></p> <ul> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">Deep expertise in mathematical optimization and recommendation algorithms applied to large-scale matching or marketplace problems.</span></li> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">Judgement about when to reach for simple statistics, classical ML, LLMs, or agentic approaches.</span></li> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">5+ years applying ML, AI research, optimization, or recommendation systems to complex production problems.</span></li> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">Python skills sufficient to build, test, and iterate on working prototypes independently.</span></li> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">Able to take a loosely defined product or customer problem and turn it into clear hypotheses, experiments, and metrics.</span></li> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">You must be comfortable working on ambiguous problems and suggesting solutions rather than waiting to be told exactly what to do.</span></li> </ul> <p><span style="font-family: tahoma, arial, helvetica, sans-serif;"><strong>Nice to have</strong></span></p> <ul> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">An MSc or PhD in Computer Science, Maths, Statistics, Economics, Psychology, ML, or a related field—or equivalent knowledge gained another way.</span></li> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">Experience working alongside product and engineering teams.</span></li> </ul> <p style="text-align: center;"> </p> <p style="text-align: center;"><span style="color: rgb(126, 140, 141); font-family: tahoma, arial, helvetica, sans-serif;"><em>How you'll work</em></span></p> <ul> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">You'll join an established Supply, Data Science team, working alongside existing specialists (for example, in marketplace economics). </span></li> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">You don't need to have all the answers on day one, but you should be ready to get stuck in quickly.</span></li> <li style="font-family: tahoma, arial, helvetica, sans-serif;"><span style="font-family: tahoma, arial, helvetica, sans-serif;">You spot problems worth solving and start on them, rather than waiting to be assigned.</span></li> <li style="font-family: tahoma, arial, helv