Sr Scientist, Tech - Science

Every day thousands of merchants use our Offers platform to reach users on Uber to grow their businesses. The Science team on Offers designs and builds the core algorithmic components of this system.
As a Senior Scientist on the team, you will work on understanding how various parts of the offers system (e.g. offer types, eater preferences, merchant profiles) are impacting the effectiveness of Offers. You will lead the design and implementation of new algorithms to make our Offers system more efficient and performant. You will also work on the interaction of offers with the different marketing levers available to merchants, like ads.
We are looking for experienced candidates, who have had extensive experience building with causal inference techniques, advanced statistics and experimentation. The ideal candidate should possess a strong passion for understanding complex systems, have the curiosity to understand why systems behave in certain ways, have the drive to research / propose new system designs
What You Will Do -
Use statistical and causal inference techniques to measure success, develop northstar metrics and KPIs to help provide a more rigorous data-driven approach in close partnership with Product and other subject areas such as Offers for Uber Eats
Design experiments and interpret the results to draw detailed and impactful conclusions.
Collaborate with data scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines.
Develop data-driven business insights and work with cross-functional partners to find opportunities and recommend prioritisation of product, growth, and optimisation initiatives
Present findings to senior leadership to drive business decisions
Basic Qualifications -
Undergraduate and/or graduate in Math, Economics, Statistics
7+ years experience as a Data/Applied Scientist with strong background in experimentation
Knowledge of underlying mathematical foundations of statistics, hypothesis testing, experimentation, causal inference, measurement science and constrained optimization
Ability to use a language like SQL, Python or R to work efficiently at scale with large data sets