Full-Time

Fraud Analyst

Updated on 6/24/2026

Prolific

Prolific

1,001-5,000 employees

Platform matching researchers with study participants

No salary listed

United Kingdom

Hybrid

Some travel to London required.

Category
Data & Analytics (1)
Required Skills
Data Science
SQL
Machine Learning
Data Analysis
Requirements
  • This role is a hands on Fraud analyst role for a stand out candidate with strong critical thinking, AI- and data-literacy, and a huge amount of drive.
  • Extreme Ownership: You’re the type of person who sees a "huge hole" and immediately starts filling it. You don't wait for a ticket to tell you something is wrong; you dive in and find the root cause.
  • The "Investigator" Mindset: You enjoy the "whodunnit" aspect of fraud. You can spot patterns, cross-reference multiple data points, and remain objective when a participant claims the system made a mistake.
  • Aspiring Data Literacy: You don’t need to be a Data Scientist, but you should have a hunger to become data-literate. You’re comfortable (or willing to learn) diving into databases and collaborating with technical teams to get the answers you need.
  • Practical Communication: You can take a complex technical ban and explain the "why" to a researcher or support agent in a way that is clear, firm, and helpful.
  • Adaptability: The fraud landscape changes every week (especially with LLMs and bots). You’re excited by the idea of a role that evolves and offers room to grow into more technical or strategic areas as you settle in.
  • Systems Thinking: You understand that a marketplace is an ecosystem. You have the ability to foresee how tightening a rule on the participant side might accidentally impact the researcher experience, or how an engineering change might shift fraud to a different part of the product.
  • A "Trust but Verify" Mentality: You possess a healthy dose of skepticism. You default to assuming positive intent from our users, but you rely on hard data and undeniable proof before closing a case.
Responsibilities
  • Crossfunctional Problem Solving: You’ll work with Data Science, Product, Engineering, Support, and Human Data teams every day.
  • Deep-Dive Investigations: You’ll review data quality reports from researchers, cross-referencing participant IDs against our internal data to validate fraud claims. You’ll recommend a response to the researcher and ensure that bad actors are restricted based on your findings.
  • Second-Line Expert Support: You’ll act as the escalation point for our Support team. You’ll handle the tricky edge cases, ban appeals, and "system-says-no" moments where human judgment is needed to override or validate the algorithm.
  • Sonar Audits & Prevalence Tracking: You will lead our "Sonar" reviews - a regular audit of our participant network. Your work here directly generates our "bad actor prevalence" and "fraudulent submission" metrics, which are the primary KPIs for how we track our success against fraud. The other side of the coin - you’ll audit our ban decisions to measure fairness and participant experience through overturn rates.
  • Model Training & Feedback Loops: You’ll partner closely with Data Science to review "high risk" participants flagged by our fraud models. Your manual reviews will provide the vital "golden set" of data that allows us to tweak and improve our ML models.
  • Operational Innovation: We don’t want you just to follow the process - we want you to break and fix it. You’ll be constantly looking for ways to automate your own tasks, suggest product features to the engineers, and make life easier for our Support team.
  • Policy Design & Refinement: As you encounter edge cases and new fraud vectors, you won't just solve the immediate ticket. You will write, refine, and document the internal policies and standard operating procedures that govern how our platform defines "acceptable use."
  • Balancing Friction vs. Growth: You will be a key voice in the room when Product launches new features. You'll advise on potential fraud loopholes and help strike the delicate balance between keeping bad actors out and keeping the onboarding experience seamless for good participants.
Desired Qualifications
  • Familiarity with AI training data workflows, labeling platforms, or crowdsourcing tools is a strong advantage.

Prolific operates an online research platform that connects researchers with a global pool of vetted participants. Researchers post studies and set demographic criteria to recruit eligible participants, who complete surveys and other research tasks to earn compensation. The platform uses a reputation-based system to ensure data quality from both researchers and participants. Clients include academic institutions, businesses, and individual researchers, making Prolific a centralized marketplace for human data in online research. The business model charges researchers a commission for each study conducted on the platform, covering participant recruitment, study management, and platform upkeep. Overall, Prolific aims to provide a reliable, efficient way to collect high-quality data for research and market insights.

Company Size

1,001-5,000

Company Stage

Series A

Total Funding

$33.3M

Headquarters

London, United Kingdom

Founded

2014

Your Connections

People at Prolific who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • AI training demand surge drives growth as companies require reliable human data for model development and testing.
  • Custom screening automation and participant allowlists reduce researcher friction and increase platform stickiness.
  • Series A funding enables geographic expansion and product development to capture emerging markets beyond academia.

What critics are saying

  • Scale AI and MTurk's cost advantage erodes market share in price-sensitive AI training and annotation segments.
  • EU AI Act enforcement starting August 2026 imposes strict compliance costs and participant data audit requirements.
  • Fraud rings exploiting screener systems damage researcher trust and inflate participant rejection rates significantly.

What makes Prolific unique

  • Prolific's reputation-based system and 120,000 vetted participants ensure higher data quality than competitors like MTurk.
  • Advanced screener logic with AND/OR conditions enables precise participant targeting for complex research requirements.
  • Established relationships with Google, Stanford, Oxford, and European Commission provide credibility and recurring revenue.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

-7%

1 year growth

-9%

2 year growth

-8%
StartupCentrum Media
Jul 16th, 2023
Weekly startup ecosystem overview in europe / July 10 – 15

SMART-Photonics, a pure-play foundry for Indium Phosphide photonics semiconductors, has raised €100 million in debt-financing round from Rabobank, Innovation Industries, Government of the Netherlands, ASML, Brabant Development, VDL Groep, KPN Ventures, PhotonDelta and NXP Semiconductors.

FinSMEs
Jul 14th, 2023
Prolific raises £25m in funding

Prolific, a London, UK-based provider of a platform that matches AI developers with engaged and verified people, raised £25M in funding.

Tech Company News
Jul 12th, 2023
Prolific secures $32M funding to enhance AI Training and Testing

London-based startup Prolific has raised $32 million to further develop its unique system that uses a network of 120,000 human participants to train and stress-test AI models.

Chicago News Daily
Jul 12th, 2023
Chicago News Daily - Prolific raises $32M to use people to train and test AI models

Prolific, a company that was founded to source verified data from human participants, said today that it has raised $32 million in a Series A funding round co-led by Partech and Oxford Science …

TechCrunch
Jul 11th, 2023
Prolific Raises $32M To Train And Stress-Test Ai Models Using Its Network Of 120K People

AI, when it works well, can feel like magic, but all too often AI-based systems don’t work as they should: If the data used to train models is not deep, wide and reliable enough, any kind of curveball can send that AI in the wrong direction. A London startup called Prolific has built a system it believes can help head off that issue, by tapping a network of 120,000 human participants to inform and stress test AI models. And in a sign of demand for its services, Prolific has now raised some funding — £25 million ($32 million) — to expand its operations.The round was co-led by Partech and Oxford Science Enterprises (OSE).Prolific was founded in 2014 and already counts organizations like Google, Stanford University, the University of Oxford, King’s College London and the European Commission among its customers, using its network of participants to test new products, train AI systems in areas like eye tracking and determine whether their human-facing AI applications are working as their creators want them to. Up to now, it’s been revenue from users like these that have helped Prolific grow. In fact, the only money Prolific had raised prior to this round was a seed round of $1.4 million it got after going through YC. (Yes, it was profitable; no longer now that it’s taking VC money and investing in growth.)“We’ve seen incredible traction recently, and have a huge opportunity in front of us so are taking on this new funding to supercharge our efforts and expand our product, and range of participants, much faster than we could have without it,” Phelim Bradley, the founder and CEO, said over email to TechCrunch.The company was conceived initially not out of a specific need in the world of AI, but out of a general problem that researchers often face with panels for anything, something Bradley identified in his own academic work (his background, before Prolific, was in computational biology and physics).In short, it’s a challenge to find comprehensive cross sections of people to respond to questions, and nearly impossible to do so in a timely manner