Lead Data Scientist

Zego
London
1 day ago
Create job alert

Description

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 Lead Data Scientist, reporting to the Head of Data Science, to be a pivotal contributor to our Core Pricing team. The mission is to build and run a world-class data-science operating model that turns ideas into production-grade pricing and risk models fast, safely, and repeatedly.

Key Responsibilities

  • Lead the building and scaling of next-generation risk models, overseeing everything from creative feature discovery and advanced modeling to robust pipeline deployment and long-term R&D strategy
  • Establish a reliable Data Science workflow: clear guard-rails, templates, and documentation across the full project lifecycle
  • Shorten the idea-to-production cycle: from first data pull to live rate change
  • Foster a culture of collaborative experimentation: pairing Pricing, Data Science, Machine Learning Engineering & Systems Engineering
  • Line management and mentorship: manage 2  Data Scientists and mentor members of the team and help them in their development
  • Define coding standards and best practice, map common processes and establish playbooks for them
  • Help decide on tooling used during the Data Science project lifecycle

Required Skills

  • Education: Bachelor’s or Master’s degree in Statistics, Mathematics, Actuarial Science, Data Science or related field
  • Experience: At least 5 years proven experience in insurance pricing and applied ML, including leading projects and people, with a particular focus on Data Science operations
  • Technical Skills:
    • Python Proficiency: Strong Python programming skills, with experience in developing and maintaining analytics packages and tools. Familiarity with data science libraries such as pandas and scikit-learn
    • SQL: Proficient in SQL, particularly with cloud data warehouses like Snowflake
    • Statistical Methodology: In-depth knowledge of GLMs and other machine learning algorithms
    • Data Tools: Familiarity with cloud-based data platforms (we’re on AWS) and data visualisation tools (Looker, matplotlib, seaborn)
  • Software Engineering: 
    • Experience with version control systems (e.g., Git), CI/CD pipelines, and software development best practices in a data-intensive environment
    • Ability to balance architecture thinking with heads-down coding
  • Soft Skills: 
    • Excellent communication and project management skills, with a proven ability to work collaboratively across teams and present complex information in a clear, accessible way
    • Care about documentation, reproducibility, and teaching others “the why” behind decisions

Nice To Have

  • Exposure to telematics or usage-based insurance data
  • Experience designing or maintaining MLOps platforms
  • Hands-on experience with insurance pricing tools like Akur8, Emblem or similar pricing modelling tools

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.

#LI-IL1

#LI-Hybrid

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

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

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.