At a Glance
- Tasks: Lead a team to solve core problems in Payments & Lending using machine learning.
- Company: Cleo empowers financial well-being through innovative AI solutions, backed by top investors.
- Benefits: Enjoy flexible work, generous leave, private medical insurance, and a supportive culture.
- Why this job: Make a real impact on users' financial lives while growing in a dynamic, trusted environment.
- Qualifications: Extensive experience in ML model deployment and managing high-performing teams required.
- Other info: We celebrate diversity and encourage applications from all backgrounds.
The predicted salary is between 43200 - 72000 £ per year.
Machine Learning Engineering Manager – Payments & Lending
Location: London
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 Cleo
Most 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 utilize this feature. The team focuses on understanding user cash flow, including payment data and risk profiles – this data is then modeled to work out credit risk for each user.
Responsibilities
- Understanding core problems faced by our Payments & Lending team and leading the team to overcome them – this could include understanding user 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 behavior.
- Impacting Cleo’s bottom line through improving our lending eligibility and decisioning systems.
- Responsible for people management of the data scientists & ML engineers in your squads, coaching and developing them to deliver on the roadmap.
- Building out the headcount plan and being 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 Haves
- Experience 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.
Company Culture
Cleo is a culture of stepping up. We want, and expect you to grow and develop. That means trying new things, leading others, challenging the status quo, and owning your impact. You’ll have our support in everything you do. But more importantly, you’ll have our trust.
We treat you as humans first, employees second. Because we can’t fight for the world’s financial health if we’re not healthy ourselves. This means the usual perks but it also means flexibility. We take pride in being a flexible workplace that trusts our Cleople to deliver their best work, giving you the autonomy to structure your day around morning drop-offs to school or daily dog walks.
Benefits
- Generous pay increases for high performers and for high-growth team members.
- Equity top-ups for team members getting promoted.
- 25 days annual leave a year + public holidays (+ an additional day for every year you spend at Cleo).
- 6% employer-matched pension in the UK.
- Performance reviews every 8 months.
- Private Medical Insurance via Vitality, dental cover, and life assurance.
- Enhanced parental leave.
- 1 month paid sabbatical after 4 years at Cleo.
- Regular socials and activities, online and in-person.
- We’ll pay for your OpenAI subscription.
- Online mental health support via Spill.
- And many more!
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Machine Learning Engineering Manager - Payments & Lending employer: Tbwa Chiat/Day Inc
Contact Detail:
Tbwa Chiat/Day Inc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineering Manager - Payments & Lending
✨Tip Number 1
Familiarize yourself with Cleo's mission and values. Understanding how we empower users to achieve financial well-being will help you align your experience and ideas with our goals during discussions.
✨Tip Number 2
Highlight your experience in building and deploying machine learning models, especially in the context of payments and lending. Be ready to discuss specific projects where you've made a measurable impact on business outcomes.
✨Tip Number 3
Prepare to showcase your leadership skills. As a Machine Learning Engineering Manager, you'll be responsible for managing teams. Think of examples where you've successfully coached or developed team members.
✨Tip Number 4
Stay updated on the latest trends in machine learning and financial technology. Being able to discuss recent advancements or research can demonstrate your passion and proactive approach to influencing the ML roadmap at Cleo.
We think you need these skills to ace Machine Learning Engineering Manager - Payments & Lending
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Machine Learning Engineering Manager position. Tailor your application to highlight relevant experiences that align with Cleo's focus on payments and lending.
Highlight Relevant Experience: In your CV and cover letter, emphasize your extensive experience in building and deploying machine learning models, as well as your ability to manage and develop high-performing teams. Use specific examples to demonstrate your impact in previous roles.
Showcase Technical Skills: Make sure to mention your proficiency in Python and SQL, as well as any experience with AWS technologies or container orchestration tools. This will help you stand out as a candidate who can contribute immediately to Cleo's projects.
Communicate Effectively: Since the role requires communicating findings to non-technical stakeholders, include examples in your application that showcase your ability to convey complex information in a clear and engaging manner. This will demonstrate your fit for the collaborative culture at Cleo.
How to prepare for a job interview at Tbwa Chiat/Day Inc
✨Understand the Core Problems
Before the interview, take some time to research and understand the core challenges faced by the Payments & Lending team. Be prepared to discuss how your experience can help address issues like user solvency and payment processing.
✨Showcase Your Technical Skills
Highlight your extensive experience in building and deploying Machine Learning models. Be ready to discuss specific projects where you wrote production-quality code in Python and SQL, and how you measured business impact through techniques like A/B testing.
✨Communicate Effectively
Since you'll be working with non-technical stakeholders, practice explaining complex technical concepts in a clear and engaging manner. Use examples from your past experiences to illustrate your points.
✨Demonstrate Leadership and Team Development
Prepare to discuss your experience in managing and developing high-performing teams. Share examples of how you've coached team members and contributed to their professional growth, as this is crucial for the role.