Lead Product Data Scientist

About Zego 🚀

At Zego, we're on a mission to do the good thing, not the insurance thing.

Insurance hasn't changed much in over a century. The way we live, work and travel has. We're building the real-time, AI-driven infrastructure that powers innovative insurance, so good drivers get cover that works the way they actually drive.

We're not just updating insurance; We're leading the AI evolution in insurance 🤖

For us, AI isn't a line on a roadmap or a buzzword on a slide. It's our operating reality, and it's how we build products that back drivers instead of the old insurance playbook.

We don't do things slowly, and we don't do bureaucracy. We back high-performance builders who want ownership, early responsibility and the chance to do the most career-defining work of their lives. You'll get the space to try things, the tools to move fast, and the room to see your ideas reach millions of drivers.

Do not take our word for it. Read what Zegons say about us on Glassdoor.

If you're ready to build the future of insurance, we're hiring.

About the team

Zego’s Data team delivers high-impact projects across the whole business - from AI tools that let anyone query data and publish dashboards in Zego Lens, to the customer insights that shape our growth strategy.

We already have established data science teams in Pricing and Telematics. This is the first data science role in our central Data team, focused on the huge untapped potential across the rest of the business - from experimentation to churn, marketing and fraud. We’re a fast-moving disruptor in insurance, driven by great tech products and data. We adopt new technology quickly - we’re AI-first, so most of our code is now written by AI and reviewed by people.

About the role

As our first Lead Product Data Scientist, you’ll shape how Zego makes its biggest product and commercial decisions. You’ll work directly with senior leaders across Product, Growth and Operations to decide where to focus, which bets to back and how we’ll know they’ve worked.

You’ll start by building the foundations - a trusted experimentation framework and customer models that tell us who to acquire, how to engage them and where to invest. As teams learn to run routine experiments themselves, your focus will shift to guiding product investment and making sure evidence, rather than intuition, drives our roadmap.

This is a senior, hands-on role with real scope to shape a new capability - and the chance to use AI to scale data science across a growing business.

What you will be doing

• Work with senior leaders to embed data science in strategy and decision making. Create and own a prioritised roadmap for where data science can have the biggest impact.

• Own Zego’s experimentation framework - design standards, power, guardrail metrics and decision rules. Coach teams to run routine experiments themselves.

• Partner with Product teams before anything is built, shaping ideas into evidence-based hypotheses and well-designed experiments. Apply causal inference where randomised tests aren’t possible.

• Build models of customer behaviour across the lifecycle - acquisition, conversion, retention, churn and lifetime value - with teams such as Marketing and Fraud.

• Use AI to scale data science across Zego, automating experiment analysis and readouts. Build self-serve tools that help teams sharpen their hypotheses.

• Take the most impactful models into production with our ML Platform team.

• Set technical direction and mentor analysts and data scientists as the capability grows.

What you’ll need

• Significant data science experience in a product-led business, with a track record of work that changed product or commercial decisions.

• Strong executive presence - you influence senior leaders, challenge decisions with evidence and explain results clearly to any audience.

• Expertise in experimentation and causal inference, with many online experiments designed and analysed.

• Experience building customer models such as churn, propensity, LTV or segmentation - and getting them used in real decisions.

• Strong Python and SQL, with confidence working AI-first (and the judgement to spot when AI output is wrong).

• Experience taking models into production on AWS SageMaker or a similar ML platform.

Nice to have

• Familiarity with experimentation or product analytics platforms such as Statsig or Amplitude.

• Experience with Snowflake, dbt and Looker or a similar modern data stack.

• Experience of marketing measurement such as media mix modelling or incrementality testing.

• A background in insurance, fintech or another regulated or subscription business.

The Zego ways of working 🏡

Teams work better with time to collaborate and space to get things done. We call it Zego Hybrid: some of us are in our office (central London or Halifax) weekly, others monthly or quarterly. It's about finding the balance between face time and focus that produces great work and a healthy life around it.

We also make a point of getting everyone in the same room. Teams come together every quarter, and once a year the whole company does, properly. It's a serious investment and consistently one of the best parts of the year.

Here is what the last one looked like.

Benefits 🎁

💰 Market-competitive salary, benchmarked against your function and reviewed every year.

🏆 Annual performance bonus, linked to company performance and your contribution.

📈 Share options, a real stake in the company and a share in the future you build

🩺 Private medical insurance.

🏖️ Pension, generous holiday, and £1,000 a year to spend on getting to the office or learning something new.

💻 Cutting-edge systems and tools, so you always have what you need to drive your impact.

Ready to do the most impactful work of your career? We want to hear from you.

Zego, leading the AI evolution in insurance.

Equal opportunities 🌈

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.