Impact-Driven Data Scientist for Fraud & Economic Crime

NatWest Group; Manchester; On-site; GBP 60,000 - 85,000; Full time

Job summary

NatWest Group in Manchester is looking for a Data Scientist in the Economic Crime Hub to design and implement data science tools that prevent fraud and scams, reduce customer harm and financial losses, and improve fraud decisioning.

You’ll work with fraud stakeholders and data teams to translate challenges into analytical questions, build scalable pipelines, and apply ML, AI and software engineering in an Agile environment to deliver measurable fraud prevention outcomes.

Qualifications

• A strong STEM degree and experience applying statistical modelling and ML to fraud or risk.
• Ability to translate business problems into analytical questions and measurable outcomes.
• Experience with data pipelines, software engineering practices and Agile development.
• Knowledge of data visualization for stakeholders and familiarity with cloud applications.
• Awareness of model monitoring and governance is desirable.

Responsibilities

• Design and implement data science tools for fraud prevention.
• Collaborate with fraud stakeholders to identify data-led opportunities.
• Develop reusable pipelines and deploy scalable solutions in Agile environments.
• Monitor model performance, data quality, and drift.
• Investigate fraud patterns and drive improvements.

Skills

Statistical modelling

Machine learning

Python

Data visualization

Cloud computing

Education

STEM degree (Math/Physics/Engineering/CS)

Tools

Python

SQL

Cloud platforms

Job description

NatWest Group in Manchester is looking for a Data Scientist in the Economic Crime Hub to design and implement data science tools that prevent fraud and scams, reduce customer harm and financial losses, and improve fraud decisioning.

You’ll work with fraud stakeholders and data teams to translate challenges into analytical questions, build scalable pipelines, and apply ML, AI and software engineering in an Agile environment to deliver measurable fraud prevention outcomes.