Machine Learning Engineering Manager - Payments & LendingLondon
We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds. If there's anything we can do to accommodate your specific situation, please let us know. About CleoMost people come to Cleo to do work that matters.
Every day, we empower people to build a life beyond their next paycheck, building a beloved AI that enables you to forge your own path toward financial well-being.
Backed by some of the most well-known investors in tech, we've reached millions of people to support them throughout their financial lives, from their first paycheck to their first home and beyond.
We're hitting headlines too.
Recently, Forbes named us as one of their Next Billion Dollar Startups, and we were crowned the 'Hottest Tech Scaleup' at the Europas.
You'll join the existing data science function here at Cleo; a thoughtful and collaborative team of dedicated data scientists, ML engineers, and analysts with significant industry experience that is at the heart of everything we do at Cleo.
You'll build and deploy production models that developers will feed directly into the product.
This position is essential in the expansion of both product and business.
We are highly data driven, whether that be understanding natural language, deriving insights from financial data, or determining which financial product is best suited to a user.
We have interesting problems to solve on an ever-increasing scale.
You'll be working on a hugely impactful workstream, focused on the decisioning process that underpins our Cash Advance product.
You'll be working on business critical projects that influence our lending policies and impact the users that utilise this feature.
The team focuses on understanding user's cashflow, including payment data and risk profiles - this data is then modelled to work out credit risk for each user.
ResponsibilitiesUnderstanding core problems faced by our Payments & Lending team and leading the team to overcome them - this could include understanding user's solvency, customer segmentation, retention, payment processing and more.Finding opportunities for model and product improvements in Cleo's extensive datasets of transactions, bank balances, and customer behaviour.Impacting Cleo's bottom line through improving our lending eligibility and decisioning systems.You'll be responsible for people management of the data scientists & ML engineers in your squads, coaching and developing them to deliver on the roadmap.You'll build out the headcount plan and will be responsible for all hiring and team development within your area to support our growth.Extensive experience building and deploying Machine Learning models to production.Experience managing and developing high performing teams of data scientists and ML engineers.A proven track record of measuring business and user impact with techniques such as A/B testing.Ability to write production quality code in Python and SQL and a willingness to be somewhat hands on.A strong ability to communicate findings to non-technical stakeholders in a concise and engaging manner.Habits of keeping abreast of the latest research and experimenting productively with new technologies.Experience proactively influencing the ML roadmap, driving new ideas with a bias for impact.Nice to havesExperience with containers and container orchestration: Kubernetes, Docker, and/or Mesos, including lifecycle management of containers.Experience working with AWS technologies such as EC2, S3, Sagemaker.Strong domain knowledge in the credit risk and/or payments space.Apply for this job* indicates a required field
First Name *
Last Name *
Email *
Phone *
Resume/CV *
Do you require visa sponsorship from Cleo to work in the UK?
Select...
Are you able to work from our London office roughly 1-2 days per week?
* Select...
What are your salary expectations?
We only ask this to make sure we're in the same ballpark before asking you to commit your time to interviewing with us.
Feel free to leave blank if you'd prefer not to answer at this stage.
*
Where did you hear about us?
*
#J-18808-Ljbffr