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Model Validation Data Scientist

NatWest Group

City of Edinburgh

Remote

GBP 55,000 - 75,000

Full time

2 days ago
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Job summary

A leading financial institution is looking for a Model Validation Data Scientist to review and validate data-driven models. This role involves developing validation frameworks, automating processes, and collaborating with stakeholders. The ideal candidate has experience in machine learning, Python programming, and a strong understanding of statistical methods. This position offers the chance to work remotely and be part of an innovative team focused on data analytics.

Qualifications

  • Practical experience in building and validating data-driven models.
  • Ability to work under pressure, individually or as part of a team.
  • Organized and thorough work habits.

Responsibilities

  • Review and validate data-driven models used in the bank.
  • Develop validation framework for Gen AI models.
  • Share findings and build consensus on risk mitigation.
  • Automate and enhance model validation activities.
  • Collaborate with model developers for value generation.
  • Develop analytics codebase by adding functionality.

Skills

Mathematical methods
Python programming
Machine learning
Statistical modelling
Data analytics
Job description

Join us as a Model Validation Data Scientist

  • If you’re a keen problem solver and you’re passionate about data, machine learning and statistics, we think you’ll enjoy a real sense of purpose in this role
  • You’ll be harnessing your mathematical prowess to validate our data-driven models and explore ways to automate and enhance their validation processes
  • It’s your chance to be part of a collaborative community of data enthusiasts, discover new algorithms, tools and data ecosystems, and develop specialist knowledge that will see you become an expert in your field – and pave the way for further career success
What you'll do

In today’s rapidly changing world, our ability to understand tomorrow and make better decisions today is key. And while we can’t see into the future, we can use data-driven models to guide our business practices, identify uncertainties and uncover valuable insights.

But reliance on models invariably presents its own risks. And as our Model Validation Data Scientist, it’ll be your job to review and independently validate our data-driven models to determine how they’re being used, their accuracy and dependencies, and the level of model risk they pose.

Day to day, you’ll be:

  • Using data and analytics to review the data-driven models that we use across our bank and
  • Developing the validation framework for Gen AI models across the bank
  • Sharing your findings with your stakeholders and building consensus on how model risks can be mitigated
  • Exploring ways to automate and enhance our model validation activities
  • Collaborating with model developers to increase the value generated by data-driven modelling
  • Developing our analytics codebase by adding new functionality, fixing issues and testing code
The skills you'll need

With practical experience of building and validating data-driven models, you’ll bring the creativity, determination and perseverance that comes with tackling ideas that are hard to understand and problems that are hard to solve.

You’ll also bring great working habits too, like being organised, thorough and painstaking in your work, great at working under pressure, and equally content working on your own or together as a team.

And you’ll bring this all together with:

  • A good understanding of the mathematical methods, concepts and assumptions that underpin machine learning, statistical modelling and artificial intelligence
  • Python programming experience and commonly used libraries in data science
  • An appreciation of the practicalities that working with real-world datasets presents, and the operational challenge of deploying data-driven models
  • Your ability to uncover and extract meaningful insights from technical results and relay these in a way that’s easy to understand

Hours: 35

Job Posting Closing Date

20/11/2025

Ways of Working: Remote First

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