Machine Learning Engineering Manager, Cleo AI

• 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

Desirable

• 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
• 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
• Understanding 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

• 1. Intro call with Talent (30-45 mins)
• 2. Technical Interview with 2 members of the Data Science team (90 mins)
• 3. ML Design Case Study Interview with 2 members of the Data Science team (60 mins)
• 4. Cross-functional Interview with Product/Engineering (45 mins)
• 5. People Management Interview with VP Technology/Engineering Manager