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.
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.
Responsibilities
- 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
Requirements
- Quantitative foundations. An MSc, or integrated MEng or MSc, in engineering, computer science, physics, mathematics or a similar field.
- Signal processing instinct. Working knowledge of digital signal processing or sensor physics.
- 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.
- 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.
Nice to haves
- Experience applying signal processing to noisy, high-frequency sensor/time-series data (GPS, accelerometer, IMU) in production
- Exposure to insurance, mobile data, or behaviour modelling
- Experience with cloud platforms (AWS), containerisation (Docker, Kubernetes), or data orchestration frameworks
- Familiarity with our ML and tooling stack: MLflow for experiment tracking, DVC for data versioning, Streamlit for internal apps and demos
What it's like to work at Zego
At Zego, we operate like a high-performing sports team. We come together as one, driven by ambition, backed by real support, and united by a shared mission to win.
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.