Senior Data Scientist
Before the detail, here's the challenge you'd help us solve.
We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.
Here’s what this particular role covers.
The Role
As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.
This means you might:
Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements
About you
Essential:
3+ years experience working in a Data Science role.
Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
Track record of influencing team direction through your findings
A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
Comfortable working asynchronously across time zones with cross-functional partners
You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.
Desirable:
Practical experience with machine learning (e.g. PyTorch). Passion to take research ideas to production.
Track record of promoting statistical rigour and experimental best practices in your prior roles.
Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
Experience working in a fast-moving tech company or startup.
This is a full-time role based in our office in London (2 days a week in the office). At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.
A quick, honest note before you apply.
Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.
If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.
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