Senior Machine Learning Engineer, Pricing

Zego
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Private Equity Consulting

Senior Data Scientist - Private Equity Consulting

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer (Manager)

Senior Geospatial Data Scientist

Senior Machine Learning Engineer, Pricing

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.

That’s why, since 2016, we’ve been on a mission to change all of that. Our mission at Zego is to offer the lowest priced insurance for good drivers.

From van drivers and gig workers to everyday car drivers, our customers are our driving force — they’re at the heart of everything we do.

We’ve sold tens of millions of policies so far, and raised over $200 million in funding. And we’re only just getting started.

Who we're looking for

We are looking for a Senior 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.

Key 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 a 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
  • 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.

Our hybrid way of working is unique. We don't mandate fixed office days. Instead, we foster a flexible approach that empowers every Zegon to perform at their best. We ask you to spend at least one day a week in our central London office. You have the flexibility to choose the day that works best for you and your team. We cover the costs for all company-wide events (3 per year), and also provide a separate hybrid contribution to help pay towards other travel costs. 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.

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. And that’s just for starters.

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.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

Technology, Information and Internet


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.