Director – Machine Learning | Financial Crime
Glasgow | Four days per week in the office
How do you take a promising machine learning model and make it work reliably within a major bank?
We’re recruiting on behalf of our client for a Director to lead its UK Financial Crime Machine Learning portfolio, covering fraud detection and transaction monitoring.
You’ll set technical direction and lead a team of data scientists, with responsibility for models from initial exploration and feature engineering through to deployment, monitoring and improvement. This is a leadership role with real technical involvement: reviewing Python code, challenging model design and making decisions about how solutions will scale.
Working with senior stakeholders across technology, compliance and the business, you’ll help decide which problems to tackle and make sure the resulting models are useful in day-to-day operations. You’ll also develop the team, set delivery standards and ensure models meet the bank’s governance and control requirements.
What you’ll bring
You’ll have experience building and deploying machine learning models in production, alongside strong hands-on Python skills. You should be comfortable with distributed computing tools such as Spark or PySpark, cloud platforms and modern MLOps practices.
Experience managing and developing data scientists is essential, as is the ability to explain technical decisions and work through competing priorities with senior stakeholders.
Financial crime experience would be useful, but we’re interested in speaking with ML leaders from other sectors who have delivered reliable models in complex environments.
Location
The role is based at our client’s Glasgow campus, with four days per week in the office.
If you’d like to discuss the role, contact Michael at mpc@barclaysimpson.com or apply with your CV.
We seek individuals from a diverse talent pool and encourage applicants from underrepresented groups to apply to our vacancies. Our commitment to fair recruitment processes means that we welcome applicants from all backgrounds, regardless of their lived experience or personal characteristics. We also invite applicants who meet most of the listed requirements, even if not all, to apply. If you require any adjustments to the application process, please let us know.
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