Lead Machine Learning Scientist Personalisation
Lead Machine Learning Scientist Personalisation
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Job Description
Were on a mission to work for everyone.
Were waving goodbye to the complicated and confusing ways of traditional banking.
After starting as a prepaid card our product offering has grown a lot in the last 10 years in the UK. As well aspersonal and business bank accounts we offer joint accounts accounts for 1617 year olds a free kids account and credit cards in the UK with more exciting things to come beyond. Our UK customers can also save invest and combine their pensions with us.
With our hot coral cards and getpaidearly feature combined with financial education on social media and our award winning customer service we have a long history of creating magical moments for our customers!
Were not about selling products we want to solve problems and change lives through Monzo
London/Cardiff/UK RemoteBenefits
About our Machine Learning Team for Personalisation:
Personalisation is central to Monzos missionto work for everyone. By delivering tailored recommendations proactive insights and intuitive experiences we help customers make better financial decisions while strengthening their connection with the bank. Every model we build directly enhances the banking experience making it more seamless engaging and rewarding.
Our Personalisation Data team brings together experts across four key disciplines: Analytics Engineers Data Analysts Machine Learning Scientists and Data Scientists. As a Lead Machine Learning Scientist youll develop models that make every customer interaction more relevant and timely ensuring they receive products and services tailored to their needs.
From intelligent recommendations and predictive insights to seamless discovery and realtime personalisation our Machine Learning Scientists tackle challenges that directly improve customer outcomes. Whether its surfacing the right savings product at the perfect moment helping customers manage their spending or simplifying financial planning our work makes banking smarter more intuitive and truly customerfirst.
What youll be working on:
A Lead Machine Learning Scientist at Monzo is a technical Individual Contributor (IC) leadership position. As a technical Machine Learning expert working with billions of rows of data stored on a modern cloud native data platform well be expecting you to leverage your deep experience of developing and deploying advanced Machine Learning models.
Your work may involve segmentation models to better understand customer behaviors contextual bandits for optimising realtime decisions or personalised ranking algorithms that improve search and discovery. Youll also build scalable explainable and responsible AI solutions that enhance trust transparency and the overall customer experience.
The technical approaches you take to help solve customer problems will be very much in your hands and well strongly encourage and support experimentation and innovation. Well be expecting you to justify and demonstrate effectiveness along the way making sure the approach meets our business and customer needs.
Your daytoday:
As a technical individual contributor youll be providing technical leadership and shipping highly impactful MLbased solutions. Youll be embedded in a cross functional product squad working closely with product managers data scientists backend engineers and designers in an agile environment. Youll also be a technical leader within the Machine Learning discipline helping to steer technical work and drive up standards.
This will involve:
- Working with stakeholders across the organization to identify and scope out the most impactful opportunities to tackle business problems in personalisation.
- Leading the design and development of advanced real time Machine Learning models for example exploring how recent advances in machine learning (neural network graphbased and sequencebased architectures LLMs) can drive improvements in our ability to deliver personalised user experiences.
- Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline leading by example and mentoring others.
- Working closely with our ML platform team to steer the ongoing development of tools to enable rapid iteration of models and optimisations of the full ML model lifecycle.
You should apply if:
What were doing here at Monzo excites you!
- You have a multiple year track record of excellence leading the development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast moving tech company
- You have experience developing and shipping state of the art ML architectures to production and delivering business impact
- Youre impact driven and excited to own the end to end journey that starts with a business problem and ends with your solution having a measurable impact in production
- You have a selfstarter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
- You have extensive experience writing production Python code and a strong command of SQL. You are comfortable using them every day and keen to learn Go lang which is used in many of our backend microservices
- youre comfortable working in a team that deals with ambiguity and have experience helping your team and stakeholders resolve that ambiguity
- you want to be involved in building a product that you (and the people you know) use every day
- you have a product mindset: you care about customer outcomes and you want to make datainformed decisions
- Youre excited about fastmoving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain
- Youre adaptable curious and enjoy learning new technologies and ideas
Nice to haves:
- Experience working on personalisation problems for consumer applications
- Commercial experience writing critical production code and working with microservices
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
- 45 minute call with hiring manager
- 1 take home task
- 3 x 1hour video calls with various team members
Our average process takes around 34 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 Please also use that email to let us know if theres anything we can do to make your application process easier for you because of disability neurodiversity or any other personal reason.
Whats 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 were 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 1000 a year for books training courses and conferences
And much more see our full list of benefits here
If you prefer to work parttime well make this happen whenever we can whether this is to help you meet other commitments or strike a great worklife balance.
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Equal opportunities for everyone
Diversity and inclusion are a priority for us and were making sure we have lots of support for all of our people to grow at Monzo. At Monzo were 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 2023 Diversity and Inclusion Report and 2024 Gender Pay Gap Report.
Were 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 dont need full or birth names at application stage
Employment Type
Full Time
