Model Risk Data Scientist

Warszawa, Poland
Permanent - Full Time
NatWest Group
Job category
Risk Policy & Frameworks - Control, Oversight & Assurance
Closing date for applications: 13/12/2020

Join us as a Model Risk Data Scientist

  • If you have experience building and validating models using real datasets, this is a fantastic opportunity join our innovative, vibrant team in our Risk function
  • You’ll be supporting with technical reviews and oversight of models used in the bank, and working with model development teams to continually drive up the value generated by data-driven modelling
  • It’s a great chance to work on your existing data skills and take advantage of our development opportunities

What you'll do

This Model Risk Data Scientist role will see you reviewing and independently validating assigned models in accordance with the bank’s policies and model standards. You’ll communicate your findings and recommendations to stakeholders and advise on how model risk can be reduced or mitigated.

As well as this, you’ll be developing solutions for automating validation activities while understanding model and data usage, quality and interdependencies across the bank.

Your role will also involve:

  • Developing the team's analytics codebase, adding functionality, fixing issues and testing code
  • Producing ad hoc analyses, presentations and documentation
  • Reviewing your colleagues’ analysis, code and reports

The skills you'll need

We’re looking for someone with an excellent grasp of mathematical methods, concepts and assumptions that underpin machine learning, statistical modelling and artificial intelligence. You should also have a good understanding of the practicalities of dealing with real world datasets and the operational challenges of deploying data-driven models.

You’ll also need:

  • A proficiency in Python and libraries commonly used for data science
  • Practical experience building and validating models using real datasets
  • The ability to extract the essential ideas underlying technical results and explain them in terms of their practical consequences
  • Excellent technical and communication skills
  • The ability to deal with ambiguity and to work autonomously