Data Scientist, Data Quality & Provenance

Requirements

• 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

Nice to Haves

• Practical experience with machine learning (e.g. PyTorch). Passion to take research ideas to production
• Track record of promoting statistical rigor 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

What You'll Be Doing

• 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

Perks and Benefits

This role is a full-time role based in Stuttgart, Germany. At Wayve, 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. We operate core working hours so you can determine the schedule that works best for you and your team.