# Lead Data Scientist at Zego

Zego is hiring a Lead Data Scientist for a remote role open to applicants in United Kingdom. Level rates it Builds AI ●●●●; you can [apply on Zego](https://jobsbylevel.com/go/41cbd0fa-292a-4504-89c7-16f8f7bb31f5?utm_medium=ai-agent).

AI Level 4, AI centrality 83 out of 100. Remote (London).

## Details

- Company: [Zego](https://jobsbylevel.com/companies/zego)
- AI level: AI Level 4 (score 83 out of 100)
- Location: Remote (London)
- Posted: September 16, 2026
- Apply: https://jobsbylevel.com/go/41cbd0fa-292a-4504-89c7-16f8f7bb31f5?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=lead-data-scientist-at-zego-613c75

## Prepare for this job

The job page lists 4 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/lead-data-scientist-at-zego-613c75

## Description

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. The team The Telematics team turns raw phone sensor data into meaningful signals about how people drive. Using signal processing and machine learning on high-frequency GPS, accelerometer, and gyroscope data, we extract the behavioural features that power Zego's understanding of driving quality, context, and risk. The role Few teams use phone sensor data to price commercial motor insurance at scale. As a Lead Data Scientist, you'll shape how millions of trips are turned into risk signals. You'll own behavioural features and algorithms from hypothesis to production, working at the intersection of data science and engineering on GPS, inertial, and other sensor data. You'll move between quick heuristics and full ML models depending on what the problem calls for. You ship code to production, not just notebooks! What you will be doing Design and build the behavioural features and factors that drive Zego's understanding of driving quality, context and risk Turn raw, high-frequency GPS, accelerometer and gyroscope data into usable signal at a scale of more than 250,000 trips a day Research new behavioural features and detection algorithms, reading the literature, testing ideas and killing the ones that do not survive contact with real data Take work from hypothesis to production, prototyping in notebooks then writing the production-grade Python and SQL that scales Choose the simplest solution that holds, rule-based when that is enough and machine learning when it is warranted Lead experiments, validate impact with data, and automate insight generation Get features into the pricing path alongside engineers, product managers and actuaries, and translate what the sensor data shows into findings non-technical colleagues can act on What you will need to be successful Quantitative foundations. An MSc, or integrated MEng or MSc, in engineering, computer science, physics, mathematics or a similar field. This is a core role and it needs strong engineering foundations Signal processing instinct. Working knowledge of digital signal processing or sensor physics. You can reason about noise, sampling, filtering and the physical meaning behind a signal, not just its numbers Production-grade delivery. A proven track record taking data science or data engineering projects into production, with strong Python and SQL (we use Snowflake) and the scientific Python stack: Polars, Pandas, NumPy, SciPy and scikit-learn. You have designed, built and maintained reliable, observable pipelines from scratch Machine learning judgement. Experience developing and evaluating ML models on tabular data, classification or regression, where the evaluation matters as much as the model choice Clear communication. You turn ambiguous problems into structured, testable ideas and share insights clearly with technical and non-technical audiences You work AI-first. You will use AI daily here, and we mean daily. You do not need to arrive an expert, but

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