Applied Scientist (Integrity) Prolific is building the human data infrastructure that powers the next generation of AI systems. As frontier AI labs scale their use of human-generated data for training, evaluation, and alignment, the way we measure quality, performance, and operational efficiency becomes increasingly important. The Role You'll join Prolific's Integrity team, which protects the platform from fraud and misuse.

This is a new role focused on verification - in particular identifying and validating high quality expert participants. This is an emerging area, so part of the role will be to shape the problem space: working with other teams to find,validate and model useful signals for participant quality. The ideal candidate will help define the right problems to solve, not just execute against a fixed brief.

The Applied Scientist role 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. How You'll Work You'll be the first data person in this area, so you'll help shape the role and create structure where there isn't much yet, with support from leadership.

You don't need to have all the answers on day one. You spot problems worth solving and start on them, rather than waiting to be assigned. You will be comfortable (and ideally enjoy) collaborating with others.

What We Are Looking For

Deep expertise in one applied ML, statistics, or data science specialism. Examples could be risk modelling, LLM detection, and reinforcement learning, 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, ML, or a related field — or equivalent knowledge gained another way. Experience working alongside product and engineering teams. Why Prolific is a great place to work We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback.

This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity.

Working for us will place you at the forefront of AI innovation, providing access to our unique human data platform and opportunities for groundbreaking research.

Benefits

, and remote working within our impactful, mission-driven culture.

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