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Data Scientist - Fraud and Survey Optimisation

JR United Kingdom
Slough
6 days ago
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Data Scientist - Fraud and Survey Optimisation, slough

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Client:Location:

slough, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

3

Posted:

22.08.2025

Expiry Date:

06.10.2025

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Job Description:

Data Scientist - Fraud & Survey Optimisation
Location: Hybrid (2 days/week in London)
Rate: £500-£550/day (Outside IR35)
Length: 3-6 months
Start: Within 2 weeks (max 4-week notice period)

About the Role

Data Scientist - Fraud & Survey Optimisation
Location: Hybrid (2 days/week in London)
Rate: £500-£550/day (Outside IR35)
Length: 3-6 months
Start: Within 2 weeks (max 4-week notice period)

About the Role

We're working with a leading research and insights business that is tackling fraudulent data submissions across large-scale survey platforms. As part of a dedicated Fraud and Optimisation team, they're looking to bring in a contract Data Scientist to build and automate models that enhance the integrity and quality of survey data delivered to clients.

You'll be joining at a pivotal time, with the team focused on identifying response anomalies and developing scalable tools to filter out invalid data - ensuring higher-quality insights across their client base.

Key Fraud Challenges

You'll help detect and eliminate these common types of fraud:

  • Out-of-Country Fraud: Participants misreporting location to qualify for region-specific surveys.

  • Identity Simulation: Individuals creating multiple profiles to access more surveys.

  • Status Inflation: Users falsely qualifying for more surveys by over-claiming attributes.

Your Contribution

  • Work with fraud analysts to understand patterns in historic and real-time data.

  • Build and automate anomaly detection models and a fraud scorecard to flag invalid responses.

  • Improve survey yield, efficiency, and data quality using statistical and machine learning techniques.

  • Attend whiteboarding and strategic sessions twice weekly (on-site in Reading or London).

Required Experience

  • Previous experience working in data science or advanced analytics roles in fast-moving or ambiguous environments.

  • Strong understanding of fraud detection, classification modelling, and data optimisation.

  • Experience working with financial, survey, or behavioural data (e.g. trading data, yield models, customer profiling).

Desired Skills and Experience

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