Data Scientist, Economic Crime Hub

Job not on LinkedIn

🔥 0 minutes ago

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

🇬🇧 UK Skilled Worker Visa Sponsor

This company has sponsored UK Skilled Worker visas in the past.

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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NatWest Group

WebsiteLinkedInAll Job Openings

10,000+ employees

🏦 Banking

💸 Finance

💳 Fintech

Banking • Finance • Fintech

NatWest Group is a leading banking and financial services organization based in the United Kingdom. The company is committed to supporting its customers and communities, focusing on building strong relationships and delivering a range of financial products and services including commercial banking, wealth management, and risk management. With a global presence across multiple continents, NatWest Group also emphasizes the importance of its employees, providing opportunities for professional development and a supportive work environment.

📋 Description

• Design and implement data science tools and methods using data to prevent fraud and scams, reduce customer harm and financial losses, and improve fraud decisioning accuracy and efficiency • Participate in the Fraud, Engineering and Data community to identify and deliver data-driven opportunities aligned with the bank’s strategic direction • Promote data literacy education with business stakeholders and support a data-driven culture • Combine statistical analysis, machine learning, generative AI and software engineering to develop practical, responsible solutions to fraud and scam challenges • Work with fraud stakeholders and customer teams to understand needs, form hypotheses and identify data-led solutions • Translate fraud and scam challenges into analytical questions and measurable outcomes • Build reusable pipelines, test changes and deploy scalable solutions in an Agile environment • Select, build, train and test machine learning models, fraud strategies and AI applications • Monitor internal and third-party fraud models for performance, data quality, drift and business effectiveness • Investigate emerging fraud patterns, unusual alerts and missed fraud events, and turn findings into practical improvements • Maintain evidence for governance, audit and regulatory review

🎯 Requirements

• Strong academic background in a STEM discipline such as Mathematics, Physics, Engineering or Computer Science • Experience with statistical modelling and machine learning techniques applied to fraud or other complex risk problems involving rare events • Ability to use data to solve business problems from hypotheses through to resolution • Experience using programming language and software engineering fundamentals • Experience of Cloud applications and options • Experience in synthesising, translating and visualising data and insights for key stakeholders • Experience in model monitoring, model-risk governance and documenting analytical decisions for review and challenge is desirable • Knowledge of how Large Language Models and agentic AI can support fraud and scam analysis, and the controls required to manage the risks of using those applications, is desirable

🏖️ Benefits

• Remote First working arrangement