Senior Data Scientist

Wayve; Sunnyvale (CA); On-site; USD 100,000 - 130,000; Full time

Job summary

Wayve in Sunnyvale is seeking a Data Scientist to generate actionable insights for their product and research teams. This position focuses on experimental methodologies over traditional models, offering a chance to influence strategies in autonomous vehicles.

The ideal candidate will have over 3 years of data science experience, strong SQL skills, and proficiency in Python or R for statistical analysis. A passion for experimentation and curiosity to develop innovative solutions in an evolving field is essential.

Qualifications

• 3+ years experience working in a Data Science role.
• Comfortable querying and building large datasets.
• Prior experience designing robust real-world experiments.
• Foundations in statistics.
• Proficient in statistical language and ML packages.
• Well-versed in summarizing and communicating findings.
• Track record of influencing team direction.
• Curious about building new solutions.

Responsibilities

• Build frameworks for complex data synthesis.
• Formulate key performance metrics for AV 2.0.
• Develop novel experimental techniques.
• Combine experiment methods with causal inference techniques.

Skills

Data Science experience

SQL proficiency

Statistical scripting language (Python or R)

Experimental design and evaluation

Data visualization and communication

Machine learning experience (e.g., PyTorch)

Job description

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

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 optimise 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 toward 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.

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non‑discriminatory.