Data Intelligence Analyst, Wayve
2 days a week in office (Kings Cross, London)
Autonomous mobility driven by AI
Posted today
Autonomous mobility driven by AI
201-500 employees
Posted today
2 days a week in office (Kings Cross, London)
201-500 employees
Company mission
To reimagine autonomous mobility through embodied intelligence.
Role
Who you are
- Strong experience with data analysis in transport, geography, or mobility contexts
- Familiarity with road and driving datasets (e.g., telematics, traffic data, mapping providers/datasets)
- Solid understanding of GIS concepts and spatial data analysis
- Proven ability to interpret complex datasets and communicate findings clearly to both technical and non-technical audiences
- Strong proficiency with BI tools and spreadsheets
- Skilled in presenting insights effectively to both engineering teams and senior stakeholders/executives
- Excellent research and critical thinking skills
Desirable
- Experience with predictive modelling or scenario forecasting
- Programming experience in Python or R for data wrangling and analysis
- Proficiency in SQL for querying large-scale datasets
- Familiarity with Databricks or other big data environments
- Experience using Looker, Power BI, or Tableau for building interactive dashboards
- Background in transportation planning, urban analytics, automotive, or logistics
What the job involves
- We are seeking a highly analytical and detail-oriented Data Intelligence Analyst to join our growing data strategy team. This role focuses on analysing driving datasets and road networks to assess current coverage of static, dynamic, and environmental conditions, and driving behaviours and scenarios
- Your work will help identify data coverage gaps and support both real-time insights and forward-looking projections that feed into new data acquisition strategies
- Analyse road and driving and road data to evaluate coverage and volume / occurrences of:
- Static infrastructure (e.g., road signs, lane markings)
- Dynamic elements (e.g., traffic flows, pedestrian activity)
- Environmental conditions (e.g., lighting, weather)
- Driving behaviours (e.g., braking, speed variability)
- Driving scenarios (e.g., merging, overtaking)
- Assess and audit current datasets to identify completeness, accuracy, and spatial/temporal gaps
- Develop both current-state summaries and future-state projections, including scenario modelling to support strategic decisions
- Use a combination of tools and platforms for analysis and visualization, including:
- Business Intelligence tools (e.g., Looker)
- Spreadsheets (Google Sheets)
- GIS software
- SQL, Python (for advanced data processing and modelling, occasional/optional)
- Present findings and insights to diverse audiences, including both technical/engineering teams and non-technical/executive stakeholders, tailoring content and delivery style appropriately
- Collaborate across teams, including partnership teams, data engineers and product managers, and transport planners, to translate analytical insights into actionable recommendations
Salary benchmarks
Our take
Wayve is developing artificial intelligence (AI) that teaches cars to drive autonomously using reinforcement learning, simulation, and computer vision. Wayve’s core premise is that the big breakthrough in self-driving cars will come from better AI brains rather than more sensors or “hand-coded” rules which it believes are highly restrictive and not at all scalable.
The company said that it trains its autonomous driving system using simulated environments and then transfers that knowledge into the real world, where it emulates how humans adapt to conditions in real time. It ultimately relies on end-to-end deep learning AI rather than hard-engineered AI. This is one of the world's hardest problems to solve, but Wayve has made an exciting start and is taking a very different approach to competitors like Uber and Waymo, who are relying more on sensors.
Following a few years of innovative breakthroughs, Wayve now has backing from high-profile investors such as Microsoft and angels, including Uber's chief scientist Zoubin Ghahramani and Pieter Abbeel, a UC Berkeley robotics professor and pioneer of deep reinforcement learning. The company's strategic partnerships with outfits like Asda and Ocado to test-run autonomous deliveries, as well as publicity through the Minister is a show of confidence in the future of Wayve's solution to autonomous driving.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 7 rounds)
May 2024
$1.1bn
SERIES C
Jan 2022
$200m
SERIES B
Total funding: $1.3bn
Company benefits
- Learning budget
- In-house chef
- Flexible Working
- Private health insurance and therapy
- Workplace nursery scheme
- Onsite bar
- Large social budgets
- Enhanced parental leave
Company HQ
London, UK
Leadership
Alex Kendall
(CEO)Has a PhD from Cambridge in Computer Vision & Robotics. Previously Research Engineer at Skydio and Advisor to Scape Technologies
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