Hybrid Principal Data Scientist: Fraud & Risk Analytics in London

Hybrid Principal Data Scientist: Fraud & Risk Analytics in London

London Full-Time 70000 - 90000 £ / year (est.) No working from home possible
NatWest Group

At a Glance

  • Tasks: Lead data analysis to tackle fraud and risk challenges using advanced methods.
  • Company: Join NatWest Group, a leader in financial services with a focus on innovation.
  • Benefits: Enjoy competitive pay, flexible working, and opportunities for professional growth.
  • Other info: Be part of a dynamic team driving impactful change in the financial sector.
  • Why this job: Make a real difference in combating fraud while developing your data science skills.
  • Qualifications: Experience in data science and strong analytical problem-solving abilities.

The predicted salary is between 70000 - 90000 £ per year.

NatWest Group is seeking a Principal Data Scientist to identify and work with data sets to tackle non-routine analysis problems, applying advanced analytical methods as needed. You’ll lead the data community and help steer opportunities that support the organisation.

Hybrid Principal Data Scientist: Fraud & Risk Analytics in London employer: NatWest Group

Coutts & Co is an exceptional employer, offering a unique opportunity to join a leading Private Banking and Wealth Management firm during a pivotal growth phase. With a collaborative work culture that prioritises professional development, employees are encouraged to influence strategic decisions while receiving support from senior leaders. The role of Managing Legal Counsel not only provides a platform for impactful legal work but also fosters an environment where innovation and efficiency are valued, making it an ideal place for those seeking meaningful and rewarding employment.

NatWest Group

Contact Details:

NatWest Group Recruitment Team

We think you need these skills to ace Hybrid Principal Data Scientist: Fraud & Risk Analytics in London

Communication Skills
SQL
Problem-Solving Skills
Python
Automation
Data Engineering
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