📍London/Cardiff/UK Remote | 💰 £157,000-210,000 + Benefits | Hear from the team ✨

⭐ About Ops Data:

Our Operations Data team consists of over 25 people across 4 data disciplines: Analytics Engineering, Data Analytics, Machine Learning, and Data Science.

In our Operations Collective, you'll have the opportunity to embed into an area that is the heart of how we work with our customers’ problems - delivering award winning customer support - and is full of data challenges. Machine Learning supports all aspects of Operations, from workforce planning to customer support experience, to enabling teams to work effectively and efficiently.

🔑 You’ll play a key role...

As a Senior Staff ML Scientist, you’ll be at the pinnacle of our Individual Contributor (IC) career track, serving as the foremost technical authority in Machine Learning within Monzo. 

You’ll shape foundational ML strategy and platforms that support Operations and influence the design and delivery of ML solutions across the business.

You will work cross-functionally with senior leadership, engineering teams, and business stakeholders to define and execute our long-term ML strategy. You’ll influence the development of Monzo’s ML capabilities across diverse areas, from automating support experiences to optimizing operational efficiency, and pioneering AI-driven products that improve customer outcomes.

Beyond technical execution, you will mentor and guide the next generation of ML talent at Monzo, elevating the standard of ML expertise across the company. You’ll also be a thought leader, influencing best practices in ML model and GenAI systems development, deployment, and governance at scale.

📌 Responsibilities:

• Define and execute the strategic vision for ML across Operations and adjacent business areas.
• Define reusable ML architectures and modelling standards adopted by multiple teams, and guide the development of complex systems that serve as the foundation for multiple products and problem spaces.
• Act as a senior technical authority, setting best practices and architectural patterns for ML across the organization.
• Collaborate with Engineering, Product, and Leadership teams to integrate ML-driven solutions into core business processes.
• Advocate for and implement responsible AI practices, ensuring fairness, robustness, and transparency in our models.
• Mentor and coach ML practitioners at all levels, fostering a culture of continuous learning and innovation.
• Engage with the broader ML community, sharing knowledge through conferences, blog posts, and open-source contributions.

🤩 We’d love to hear from you if…

• What we’re doing here at Monzo excites you!
• You have a proven track record of leading large-scale ML initiatives with tangible business impact, preferably in a fast-moving tech company.
• You have led the development and adoption of reusable ML modelling patterns, architectures, or infra across large organizations.
• You have experience developing state-of-the-art deep learning models, LLMs, and advanced AI architectures.
• You are an industry expert in ML model development, deployment, and MLOps at scale.
• You are deeply comfortable with Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch) and have experience working in a microservices architecture (Go Lang experience is a plus).
• You have extensive experience with real-time ML applications, reinforcement learning, graph-based models, and/or NLP.
• You can communicate complex ML concepts to both technical and non-technical audiences, influencing senior stakeholders and executives.
• You thrive in ambiguous, fast-changing environments and have a proactive, problem-solving mindset.
• You have a passion for mentoring, and can elevate the ML skill set across the organization influencing both cross-functional and executive strategy.

Nice to haves:

• Track record of shaping ML strategy and system design in highly-scaling support or operational environments.
• Contributions to industry standards, open source software libraries, or public thought leadership in machine learning systems.

The Interview Process:

Our interview process involves 3 main stages. We promise not to ask you any brain teasers or trick questions!

• 30 minute recruiter call 
• 1 hr call with hiring manager 
• 4 x 1-hour video calls with various team members (short presentation included) 

Our average process takes around 3-4 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on tech-hiring@monzo.com

What’s in it for you:

✈️ We can help you relocate to the UK 

✅ We can sponsor visas

📍This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London).

⏰ We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.

📚Learning budget of £1,000 a year for training courses and conferences

➕And much more, see our full list of benefits here

If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance

#LI-DC2  #LI-Remote

Equal opportunities for everyone

Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2024 Diversity and Inclusion Report and 2024 Gender Pay Gap Report.

We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.

If you have a preferred name, please use it to apply. We don't need full or birth names at application stage 😊