Data Scientist II, Experimentation

What you’ll do

• Comb through the literature in experimentation to identify potential methodologies that can improve parts of our platform where we have the biggest opportunities.
• Make the process of setting up, running and evaluating experiments smoother and more repeatable for our platform users, ensuring that decisions are risk-aware and consistent.
• Write workflows to make our vast experimentation meta-data able to be leveraged by our team and outside of our team to better understand the experimentation landscape.
• Consult with product data science teams to debug, design or improve their experiments and experimentation process.

What we’re looking for

• PhD in a relevant field (stats, applied math, biostatistics, etc…) OR 2+ years of hands-on experience working as a data scientist or applied scientist.
• Experience working directly on experimentation problems and an awareness of state of the art methodologies.
• The ability to write clean, efficient, and scalable code that can be easily maintained and extended by other team members.
• Proficiency in software development best practices, including version control systems such as Git, to ensure efficient collaboration, code management, and reproducibility in a data science environment.
• Familiarity with workflow management tools such as Apache Airflow to create and schedule data pipelines, allowing for automated and reliable execution of machine learning workflows.