Data Scientist

As a Data Scientist in the Experimentation and Product group, you will focus on generating robust, actionable insight that helps our product, data and research teams prioritise their efforts today and identify opportunities for tomorrow.

 

Rather than focusing on using black-box models to optimize ML performance, DS focus on using experimental and causal inference methods to generate statistically-robust and highly interpretable findings. This is a fascinating opportunity to pioneer data science methodologies in a very complex and novel space in AV. 

 

This means you might:

• Build the frameworks that best synthesise our complex video and simulation data, and use it to facilitate analytics-driven strategy from individual product teams all the way to the company level
• Formulate and iterate upon the performance metrics Wayve should focus on, to best measure success in an AV 2.0 world
• Develop and deploy novel experimental techniques to improve signal-to-noise ratio and reduce time to feedback
• Combine  experiment methods with offline causal inference techniques 

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Comfortable 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.
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• 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.