Senior Machine Learning Engineer (Credit Risk)
Senior Machine Learning Engineer (Credit Risk)

Senior Machine Learning Engineer (Credit Risk)

London Full-Time 48000 - 84000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join us to build and deploy machine learning models that shape financial decisions.
  • Company: Cleo is a fast-growing fintech unicorn on a mission to revolutionise money management.
  • Benefits: Enjoy competitive pay, flexible working, generous leave, and wellness support.
  • Why this job: Make a real impact in a collaborative team while tackling exciting challenges in credit risk.
  • Qualifications: Experience in data science, Python, SQL, and deploying ML algorithms is essential.
  • Other info: We value diversity and encourage applications from all backgrounds.

The predicted salary is between 48000 - 84000 £ per year.

About Cleo

At Cleo, we’re not just building another fintech app. We’re embarking on a mission to fundamentally change humanity's relationship with money. Imagine a world where everyone, regardless of background or income, has access to a hyper-intelligent financial advisor in their pocket. That’s the future we’re creating. Cleo is a rare success story: a profitable, fast-growing unicorn with over $200 million in ARR and growing over 2x year-over-year.

This isn’t just a job; it’s a chance to join a team of brilliant, driven individuals who are passionate about making a real difference. We have an exceptionally high bar for talent, seeking individuals who are not only at the top of their field but also embody our culture of collaboration and positive impact.

If you’re driven by complex challenges that push your expertise, the chance to shape something truly transformative, and the potential to share in Cleo’s success as we scale, while growing alongside a company that’s scaling fast, this might be your perfect fit.

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.

Key Responsibilities:

  • Improving our current machine learning models.
  • Work closely with credit analysts to manage our credit risk and drive improvements to our credit policies.
  • Finding opportunities for model and product improvements in Cleo's extensive datasets of transactions, bank balances, and customer behaviour.
  • 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, payment processing, and more!
  • Impacting Cleo’s bottom line through improving our eligibility and decisioning systems.

Requirements:

  • Extensive experience in data science or related roles.
  • Ability to write production quality code in Python and SQL.
  • Experience deploying machine learning algorithms into production.
  • Experience conducting A/B experiments & measuring impact.
  • Strong understanding of classification models, ideally within risk, or more broadly with imbalanced data.
  • 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 leading data science initiatives and taking ownership of services or models.
  • Experience proactively influencing the ML roadmap, driving new ideas with 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.

What do you get for all your hard work?

  • A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles.
  • A clear progression plan. We want you to keep growing. That means trying new things, leading others, challenging the status quo and owning your impact.
  • Flexibility. We can’t fight for the world’s financial health if we’re not healthy ourselves. We work with everyone to make sure they have the balance they need to do their best work.
  • Work where you work best. We’re a globally distributed team. If you live in London we have a hybrid approach, we’d love you to spend one day a week or more in our beautiful office.
  • Other benefits include company-wide performance reviews every 6 months, generous pay increases for high-performing 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, up to 30 days), 6% employer-matched pension in the UK, 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 mental health support via Spill, and many more!

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.

Senior Machine Learning Engineer (Credit Risk) employer: cleo

Cleo is an exceptional employer, offering a dynamic work environment in London where innovation meets impact. With a strong focus on employee growth, competitive compensation, and a commitment to work-life balance, Cleo fosters a culture of collaboration and inclusivity, ensuring that every team member can thrive while contributing to a transformative mission in fintech. Join us to be part of a fast-growing unicorn that values your expertise and supports your professional journey.
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Contact Detail:

cleo Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior Machine Learning Engineer (Credit Risk)

✨Tip Number 1

Familiarise yourself with Cleo's mission and values. Understanding their goal of transforming financial relationships will help you align your answers during interviews and demonstrate your passion for their vision.

✨Tip Number 2

Showcase your experience with machine learning models, particularly in credit risk. Be prepared to discuss specific projects where you've improved models or influenced decision-making processes, as this is crucial for the role.

✨Tip Number 3

Network with current or former Cleo employees on platforms like LinkedIn. Engaging with them can provide insights into the company culture and expectations, which can be invaluable during your application process.

✨Tip Number 4

Prepare to discuss your coding skills in Python and SQL. Since you'll be writing production-quality code, having examples ready to demonstrate your proficiency will set you apart from other candidates.

We think you need these skills to ace Senior Machine Learning Engineer (Credit Risk)

Machine Learning Algorithms
Python Programming
SQL Proficiency
Data Science Experience
Model Deployment
A/B Testing
Classification Models
Risk Assessment
Data Analysis
Communication Skills
Collaboration with Stakeholders
Problem-Solving Skills
Understanding of Financial Data
Experience with Imbalanced Data
Proactive Influence on ML Roadmap
Familiarity with AWS Technologies
Containerisation (Docker, Kubernetes)
Adaptability to New Technologies

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, credit risk, and data science. Use specific examples that demonstrate your ability to write production-quality code in Python and SQL, as well as your experience with deploying machine learning algorithms.

Craft a Compelling Cover Letter: In your cover letter, express your passion for transforming financial services and how your skills align with Cleo's mission. Mention your experience with A/B testing and classification models, and how you can contribute to improving their credit risk models.

Showcase Your Projects: If you have worked on relevant projects, especially those involving credit risk or machine learning, include them in your application. Describe the challenges you faced, the solutions you implemented, and the impact of your work.

Prepare for Technical Questions: Be ready to discuss your technical expertise in detail. This includes your experience with model deployment, understanding of imbalanced data, and any tools you've used like AWS technologies or container orchestration. Clear communication of complex concepts to non-technical stakeholders is key.

How to prepare for a job interview at cleo

✨Showcase Your Technical Skills

As a Senior Machine Learning Engineer, you'll need to demonstrate your expertise in Python and SQL. Be prepared to discuss your experience with deploying machine learning algorithms into production and any relevant projects you've worked on that showcase your coding abilities.

✨Understand Credit Risk Fundamentals

Since the role focuses on credit risk, make sure you brush up on classification models and how they apply to financial data. Be ready to explain your understanding of risk profiles and how you've previously tackled similar challenges in your work.

✨Communicate Effectively with Non-Technical Stakeholders

Cleo values the ability to convey complex findings in an engaging manner. Prepare examples of how you've successfully communicated technical concepts to non-technical audiences, as this will be crucial for collaborating with credit analysts and other team members.

✨Demonstrate a Growth Mindset

Cleo is looking for individuals who are eager to learn and adapt. Share instances where you've kept up with the latest research or experimented with new technologies. This shows your commitment to continuous improvement and innovation in the field.

Senior Machine Learning Engineer (Credit Risk)
cleo
Location: London
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  • Senior Machine Learning Engineer (Credit Risk)

    London
    Full-Time
    48000 - 84000 £ / year (est.)
  • C

    cleo

    50-100
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