National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

▷ (Immediate Start) Lead Data Scientist - Telematics...

Zego
London
1 day ago
Create job alert

About Zego

At Zego, we understand that traditional motor insurance holds good drivers back. It's too complicated, too expensive, and it doesn't reflect how well you actually drive. Since 2016, we have been on a mission to change that by offering the lowest priced insurance for good drivers.

From van drivers and gig workers to everyday car drivers, our customers are the driving force behind everything we do. We've sold tens of millions of policies and raised over $200 million in funding. And we’re only just getting started.

About the team

We don’t build pricing models, we build the driving intelligence that feeds them. Our mission is to drive safer roads and fairer insurance through data.

The Telematics team transforms raw phone sensor data into meaningful insights about how people drive. Using advanced signal processing and machine learning, we process high-frequency data to extract behavioural signals that power our understanding of driving quality, context, and risk.

About the Role

As a Lead Data Scientist, you’ll drive the technical direction of our behavioural modelling work. You’ll lead the development of telematics features from idea to production, including exploratory analysis, signal design, risk evaluation, and scalable deployment.

This is a hands-on leadership role where you’ll design solutions, mentor other scientists, influence architecture across systems, and guide decision-making in uncertain or complex contexts.

We’re looking for an applied scientist - someone who thrives on getting things into production, values strong engineering, and has opinions on building reliable, scalable systems.

What you will be doing

  • Drive the development of telematics features from mobile sensor data, including project design, modelling, validation, and deployment.

  • Conduct deep dives into driving signals, develop hypotheses, and evaluate their predictive power for risk.
  • Design technical solutions with clear trade-offs around performance, scalability, and maintainability.

  • Collaborate closely with data engineers, software engineers, mobile developers, and PMs to deliver production-grade features.

  • Mentor data scientists, set high standards for technical quality, and promote knowledge sharing and learning.

  • Own delivery of large, complex projects, breaking them into milestones, planning collaboratively, and unblocking teams.

  • Contribute to Request For Comments (RFCs), design reviews, and technical discussions and initiatives with high technical ambiguity.

  • Ensure that our models and features are observable, tested, and continuously improving.

  • Help shape the team roadmap and longer-term strategy for behavioural signal development.

    About You

  • MSc or equivalent industry experience in a relevant field (e.g. Computer Science, Engineering, Physics, Statistics). A PhD is welcome but not required.

  • Experience delivering production-grade data science or engineering solutions, including design, implementation, and deployment

  • Strong proficiency in Python and SQL, with practical experience in designing and implementing efficient data pipelines, including performance tuning and optimization.

  • Proven ability to apply machine learning techniques to real-world problems. Familiarity with core libraries such as Pandas, NumPy, Scikit-learn, SciPy, and Polars is expected.

  • Experience with digital signal processing, mobile sensor physics, or behavioural signal design.

  • Proven track record of designing and delivering scalable data products, driving cross-functional initiatives, and influencing architectural decisions.

  • Strong communicator, skilled at translating between technical and non-technical audiences, and building alignment.

  • A growth mindset: open to feedback, committed to continuous learning, and eager to help others develop.

    Nice to Have

  • Experience leading applied ML projects end-to-end, with a focus on code quality, runtime efficiency, and measurable impact.

  • Familiarity with cloud platforms (e.g. AWS), containerisation (Docker, Kubernetes), and orchestration tools.

  • Experience mentoring and coaching other data scientists and setting technical direction in high-impact domains.

  • Background in mobility, insurance, user behaviour modelling, or driver risk analytics.

    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

Related Jobs

View all jobs

▷ (3 Days Left) Pricing Data Scientist (Remote)...

▷ Apply Now: Data Engineer - London/Hybrid - TWE41666...

▷ High Salary: Senior CRM Data Scientist...

▷ (Apply in 3 Minutes) Senior Data Scientist - London - Hybrid Working...

▷ (01/07/2025) Senior Risk Analyst (AI, Artificial Intelligence, Machine Learning, ML, LLM, Python, SQL, London)...

▷ [Immediate Start] Data Engineer (Football Club)...

National AI Awards 2025

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 to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.