Director of Machine Learning

Barclay Simpson; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

The role leads the UK Financial Crime ML portfolio, covering fraud detection and transaction monitoring, based at Glasgow with four days per week in the office.

You will set technical direction, review Python code, guide deployment and governance, develop the team, and work with senior stakeholders across technology, compliance and the business to deliver reliable models.

Qualifications

• The candidate has experience building and deploying ML models in production.
• Strong hands-on Python skills are essential.
• Experience with distributed computing tools such as Spark or PySpark.
• Experience with cloud platforms and modern MLOps practices.
• Experience managing and developing data scientists.
• Ability to explain technical decisions to senior stakeholders.
• Financial crime experience is useful but not mandatory.

Responsibilities

• Lead UK Financial Crime ML portfolio including fraud detection and transaction monitoring.
• Set technical direction and lead a team of data scientists.
• Oversee models from exploration to deployment, monitoring and improvement.
• Review Python code and model design; ensure scalable solutions.
• Collaborate with senior stakeholders across technology, compliance and business.
• Develop the team, set delivery standards and governance.

Skills

ML production

Python

Spark/PySpark

Cloud platforms

MLOps

Data science leadership

Stakeholder management

Tools

Spark/PySpark

Cloud platforms

MLOps

Job description

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.