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Lead Machine Learning Engineer

Lead Machine Learning Engineer

ZegoCity Of London, England, United Kingdom
5 hours ago
Job type
  • Full-time
Job description

Overview

At Zego, we know that traditional motor insurance holds good drivers back. It’s too complicated, too expensive, and it doesn't take into account how well you actually drive. Since 2016, our mission has been to offer the lowest priced insurance for good drivers. From van drivers and gig workers to everyday car drivers, our customers are at the heart of everything we do. We’ve sold tens of millions of policies and raised over $200 million in funding. We’re only just getting started.

Who we're looking for

We are looking for a Lead Machine Learning Engineer to play a key role in our Core Pricing team. You will drive innovation by optimising and automating pricing processes to enable faster, more accurate decision-making. Your work will focus on developing and maintaining tooling and frameworks that enhance the efficiency of our predictive models, reducing deployment times, increasing scalability, and improving model performance through regular updates and monitoring. You will work closely with our Data Scientists, Actuaries, and Product team to deliver scalable, production-grade ML systems.

Responsibilities

  • Build model lifecycle tooling (deployment, monitoring and alerting) for our predictive models (for example claims cost, conversion, retention, market models)
  • Maintain and improve the development environment (Kubeflow) used by our Data Scientists and Actuaries
  • Develop and maintain pricing analytics tools that enable faster impact assessments, reducing manual work
  • Collaborate with the technical pricing, street pricing and product teams to gather requirements and feedback on tooling and to build impactful technology
  • Communicate complex concepts to technical and non-technical stakeholders through clear storytelling

Required Skills

  • Education : Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science or related field
  • Experience : Proven experience in ML model lifecycle management
  • Core Competencies :
  • Model lifecycle : You’ve got hands-on experience with managing the ML model lifecycle, including both online and batch processes
  • Statistical Methodology : You have worked with GLMs and other machine learning algorithms and have in-depth knowledge of how they work
  • Python : You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn
  • Tooling & Environment :
  • DevOps : You have experience working with DevOps tooling, such as gitops, Kubernetes, CI / CD tools (we use buildkite) and Docker
  • Cloud : You have worked with cloud-based environments before (we use AWS)
  • SQL : You have a good grasp of SQL, particularly with cloud data warehouses like Snowflake
  • Version control : You are proficient with git
  • Soft Skills :
  • You are an excellent communicator, with an ability to translate non-technical requirements into clear, actionable pieces of work
  • You have proven your project management skills, with the ability to manage multiple priorities
  • You have worked closely together in cross-functional teams, including with Data Scientists, Actuaries, and Product Managers
  • Nice To Have

  • Experience in UK motor insurance
  • Telematics Data : Familiarity with behavioural driving data and its application in insurance pricing
  • Understanding of pricing modelling tools such as Akur8 or Emblem
  • Experience with IaC (we use Terraform)
  • Experience with gRPC / protobuf
  • What’s it like to work at Zego?

    Joining Zego is a career-defining move. People go further here, reaching their full potential to achieve extraordinary things.

    We’re spread throughout the UK and Europe, and united by our drive to get things done. We’re proud of our company and our culture – a friendly and inclusive space where we can lift each other up and celebrate our wins every day.

    Together, we’re setting the bar higher, delivering exceptional work that makes a difference. Our people are the most important part of our story, and everyone here plays a role. There’s loads of room to learn and grow, and you’ll get the freedom to steer your career wherever you want.

    You’ll work alongside a talented group who embrace each other's differences and aren’t afraid of a challenge. We recognise our achievements, learn from our mistakes, and help each other to be the best we can be. Together, we’re making insurance matter.

    How we work

    We believe that teams work better when they have time to collaborate and space to get things done. We call it Zego Hybrid. We ask you to spend at least one day a week in our central London office. We think it’s a good mix of collaborative face time and flexible home-working, setting us up to achieve the right balance between work and life.

    Our approach to AI

    We believe in the power of AI to meaningfully improve how we work - helping us move faster, think differently, and focus on what matters most. At Zego, we encourage people to stay curious and intentional about how AI is leveraged in their work and teams to drive practical impact every day. This is your chance to do the most meaningful work of your career - and we’ll provide you with the tools, support, and freedom to do it well.

    Benefits

    We reward our people well. Join us and you’ll get a market-competitive salary, private medical insurance, company share options, generous holiday allowance, and a whole lot of wellbeing benefits. We also offer an annual flexible hybrid working contribution, which you can use to support with your travel to the office or towards your own personal development. And that’s just for starters.

    There’s more to Zego than just a job - Check out our blog for insights, stories, and more.

    We’re an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, or disability status.

    #J-18808-Ljbffr

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