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Prolific

Applied Scientist (Integrity)

London
Posted about 22 hours ago
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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.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

  • 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.

You don't need to meet every point above to apply. If you have strong depth in the essentials and are interested in the work, we'd like to hear from you — we know good candidates, particularly from underrepresented groups, often hold back unless they match everything. We're happy to adjust any part of the interview process to work better for you — just let us know what would help.

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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. Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission-driven culture.

Links to more information on Prolific

  • Benefits
  • External Handbook
  • Website
  • Youtube
  • Privacy Statement

By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.

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Skills

Applied Machine Learning
Statistics
Data Science
Risk Modelling
LLM Detection
Reinforcement Learning
Python
Prototyping
Experimental Design
Metric Definition

Location

London, England, United Kingdom

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