Remote Senior Machine Learning Scientist, Borrowing
Role details
Job location
Tech stack
Job description
The mission of Borrowing ML Scientists is to improve the customer and business outcomes through better automated decisioning, using Machine Learning and Statistical modelling. We have a primary focus in credit risk modelling, with our expertise also applied to predict and optimise utilisation, pricing, collection and marketing.
You will be working alongside a team of very experienced and highly efficient ML Scientists, with well established toolings for the fully lifecycle of ML models. Each of you owns multiple ML applications end-to-end, from experiment design and data curation, to deployment and monitoring. You will be empowered to innovate in the data, methodologies and toolings, so we can build better models easier and faster.
You will have exposure to all Borrowing products and applications, with autonomy to decide what are the most impactful topics to work on, and how to deliver them. You will work closely with our Credit Strategy Managers, Model Validation Analysts, Backend Engineers, and Product Managers, to fit your model development into the product roadmap. You are also empowered to think big about the business, market and customers, to influence our product and credit strategy beyond just the world of models.
Our technology stack
We rely heavily on the following tools and technologies (although we do not expect applicants to have prior experience of all them):
- Google Cloud Platform for all of our analytics usages
- BigQuery SQL and dbt for our data modelling and warehousing
- PyData stack for model development and offline deployment
- Google Vertex AI platform for cloud computing
- AWS for backend infrastructure
- Python for ML model microservices
- Go lang for most other microservices
- AI toolings for productivity (an evolving list)
- Google suites including access to Gemini
- ChatGPT enterprise
- Claude code
Requirements
- You are result oriented and motivated by the impact on our customers and business
- You enjoy a high degree of autonomy and thrive in a fast-paced environment
- You are keen to grow your knowledge in both business and technology
You must have:
- Excellent SQL and Python skills with good understanding of best practices in software engineering and data engineering
- In-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etc
- Solid knowledge of statistics: hypothesis testing, confidence intervals, bootstrap
- Experience of end-to-end model development and maintenance of ML models used for business critical automated decisioning, in a consumer facing industry
- Great attention to details while keeping an eye on the big picture
- Excellent communication skills to articulate complex problems
- Capability to build mutual respect and trust with people of different background
Nice to have:
- Experience in UK/EU retail lending businesses for personal/business customers
- Experience of ML model governance in a regulated industry
- Experience in leverage modern day AI tools for productivity
Benefits & conditions
£86,000 to £105,000 plus stock options & benefits
We can help you relocate to the UK
We can sponsor visas
This role can be either based in our London office with hybrid working pattern, or fully remote within UK with occasional travels to London.
We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup.
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 books, training courses and conferences
And much more, see our full list of benefits here
#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.