{
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  "job_title": "Senior Data Scientist (FinCrime / Fraud)",
  "job_country": "GB",
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  "job_latitude": 55.378051,
  "job_location": "United Kingdom",
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      "publisher": "LinkedIn",
      "apply_link": "https://uk.linkedin.com/jobs/view/senior-data-scientist-fincrime-fraud-at-wave-group-4383179165?utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
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  "employer_name": "Wave Group",
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  "job_posted_at": "6 days ago",
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  "job_description": "💻 Job Title: Senior Data Scientist (AI / ML Engineer)\n\n💰 Salary: up to £135k (+ very generous early-stage equity, £100k+)\n\n📍 Location: Central London, EC1 (3 office day/week)\n\n🏦 Company: B2B FinTech / Fraud Prevention\n\n👥 Employees: ~25\n\n💸 Funding: $15m+ (Series A)\n\nThis London startup is building a new intelligence layer designed to bring more context and security to digital payments. Their technology analyses transactions in real time, gathering signals from multiple sources to determine whether a payment is legitimate or potentially fraudulent.\n\nThe platform combines distributed data systems, real-time investigations and AI-driven decisioning to help financial institutions detect scams while allowing legitimate payments to flow without unnecessary friction. Within 2 years of being founded, they're working with most Tier 1 banks and payment providers in the UK - and are just getting started!\n\nThey are now looking for an experienced Data Scientist (AI/ML Engineer) with deep fraud or financial crime experience (ideally APP fraud exposure) to join at an early stage and help shape the core intelligence powering the platform.\n\nKey responsibilities:\n• Designing and deploying machine learning models used to detect fraud and financial crime in payment flows\n• Building features from heterogeneous data sources, including transaction data, contextual signals and unstructured information\n• Improving systems that extract useful signals from fragmented or unstructured data sources\n• Building reliable ML infrastructure to train, deploy and monitor models in production environments\n• Working closely with product and engineering teams to ensure models improve real-world fraud outcomes\n• Identifying the fraud signals, typologies and data sources that meaningfully improve detection capability\n• Experimenting with both classical ML techniques and newer AI approaches where appropriate\n• Helping shape data strategy, including how feedback loops and labelling pipelines are built to improve models over time\n\nThis role is focused on shipping production systems rather than academic research.\n\n✅ Must have requirements:\n• Strong practical experience building fraud detection systems or financial crime models in production\n• Deep FinCrime / FinTech / Payments domain expertise\n• Product mindset - focus on improving real-world outcomes, not just model metrics.\n• Experience working in fast-moving environments where systems are built from scratch and priorities evolve quickly.\n• Experience working with heterogeneous datasets (transaction data, enrichment signals, text, network signals etc.)\n• Familiarity with model monitoring, drift detection and retraining pipelines\n• Strong SQL and data engineering capability\n• Strong programming skills in Python\n\n👍 Bonus points for:\n• Exposure to / understanding of APP Fraud, payment fraud or transaction monitoring\n• Previous experience working in an early stage start-up and/or high growth scale up\n• Exposure to newer approaches such as LLM-powered systems\n• Cloud infrastructure / data platforms experience, ideally GCP\n\n🛂 VISA sponsorship is available if needed.",
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  "employer_website": "https://www.thewavegroup.com",
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  "job_salary_period": "YEAR",
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  "job_employment_type": "Full–time",
  "job_employment_types": [
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  "job_posted_at_timestamp": 1773532800,
  "job_posted_at_datetime_utc": "2026-03-15T00:00:00.000Z"
}