ZEGO

ZEGO

London

Head of Telematics Data Science

Full-Time£40,000 - 60,000 per yeargisterenUnited Kingdom
IT

Job Description

Salary: £40,000 - 60,000 per year

Requirements:
  • A Masters or PhD in Data Science, Computer Science, Electrical Engineering, Physics, Mathematics or a related quantitative field, or equivalent industry research experience
  • Deep expertise in machine learning and deep learning, preferably with hands-on experience building and deploying models on high-frequency time-series sensor data
  • A strong grounding in signal processing, including signal modelling, decomposition, transforms and sensor physics
  • Experience leading and growing a data science team, developing people and delivering through others while staying close to the technical work
  • Strong software engineering practice, including Python, version control, reproducible pipelines and production-ready code
  • Experience with large-scale data processing; we use Kafka, Spark and Flink
  • The ability to explain complex technical work clearly to senior leadership, commercial teams and partners, with a bias for connecting research to business outcomes
  • Preferably, experience with on-device or embedded ML under compute and power constraints
  • Familiarity with regulated environments, or with fairness and bias in applied models, is a plus
  • You work AI-first, and are curious, experimental and able to take ownership of getting good quickly
Responsibilities:
  • Define and drive the technical roadmap, ensuring the team is working on the highest-impact problems
  • Lead the development of novel models to detect human behaviour and vehicle kinematics from high-frequency phone sensor data, on-device and in the cloud
  • Act as the primary technical authority on telematics across the business, advising on existing products, surfacing new patterns and identifying new value propositions
  • Build, grow and mentor the team, setting the technical standards needed to produce exceptional work
  • Partner with Pricing to integrate telematics predictions into risk pricing, and with Data Products and Engineering to embed telematics insight into our core products
  • Push our use of AI in analytics, model development and the driver coaching experiences we are building
  • Represent our telematics science to senior leadership, commercial teams and partners including Sompo
  • Own the metrics that track real-world model impact in production, and ensure our models meet our obligations around fair pricing
Technologies:
  • AI
  • Cloud
  • Embedded
  • Flink
  • Kafka
  • Machine Learning
  • Python
  • Spark
  • Android
  • Claude Code
  • Data Warehouse
  • Figma
  • Support
  • Marketing
  • Mobile
  • Snowflake
  • Zapier

More:

We are Zego, leading the AI evolution in insurance. We move fast with a modern tech stack and use AI across teams to remove routine work and focus on impactful delivery. Our Telematics team uses digital signal processing and machine learning to turn over a billion miles of real-world driving data into fairer pricing, safer driving and Zego Rewards. We own the full telematics stack and full pricing stack, and this role reports to the Director of Data leading three data scientists and three ML engineers. We offer a Zego Hybrid working model, with time spent in our central London office on a weekly, monthly or quarterly basis, plus quarterly team gatherings and an annual whole-company event. Benefits include a market-competitive salary, annual performance bonus, share options, private medical insurance, pension, generous holiday, 1,000 a year to spend on commuting or learning, and cutting-edge systems and tools. We are an equal opportunity employer and value diversity at our company.

last updated 36 week of 2026

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About ZEGO

ZEGO

ZEGO

London

IT

Skills & Technologies

PythonGoGitKafkaMachine LearningAIData ScienceFigmaUI

Inferred from job description

Salary Insight

£50,000

This role

£65,000

UK median

This salary is 23% below the UK median for Data roles65,000/yr).

Based on 2024–2025 UK technology sector benchmarks

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