Uber's Marketplace Engineering team creates the technology behind our ridesharing marketplace by connecting riders with drivers at the push of a button. Our solutions expand user access, deliver reliability, and provide more transportation choices to users across our global markets.
About the Role
The Experimentation Team builds self service tools for running A/B, Switchback, and Synthetic Control experiments. These allow internal customers to configure, run, and analyze experiments. Our services are in the core flow of every product launch decision at the company and as a result is in the critical path of almost every app request into Uber's services across every product. Our telemetrics generate millions of logs per second which we then process with tools like Hive and Spark to generate source of truth histories for experiment performance.
We build data science tools that work in Jupyter Notebooks and our UIs that allow for push button or sophisticated ad hoc analysis of these results by our data science customers. As a staff engineer in the XP Team you'll set the technical vision for the data systems and analysis tools within the team with deep collaboration with product, data science, and the broader Uber data ecosystem. You'll craft and build the data platform foundation for collecting billions of event logs daily powering tools and the analytics tools that allow our customers to analyze the results of A/B experiments as well as proactive monitoring of the health of experiments.
What you'll do
• Take the larger vision for A/B testing at Uber or challenge and distill it down with the leadership team into strategies and plans including trade-offs required to realize the vision.
• Work closely with the data science team to build statistically rigorous data products and distributed data systems at huge scale with state-of-the-art technology.
• Build Analysis Tools that are pleasant for data scientists to use.Represent the team in Engineering Design Reviews for the marketplace org and across Uber and be a role model for fellow engineers on both, Software Engineering principles, and on Collaboration and effective Execution.
• Actively seek out the toughest technology and engineering problems and solve them with little to no guidance.
• Be a humble mentor and trusted advisor for both our team members and the broader organization..
• Experience building large scale data pipelines, batch, or nearline systems using technologies like Hive, Spark, Flink, Samza, or similar.
• Familiarity with data science or ML frameworks such as scikit learn, tensorflow, Analytics Infrastructure, machine learning infrastructure, or similar.
• Experience working in the full lifecycle of product development from idea through delivery and support.
• BS/MS/PhD in Computer Science, Statistics or a related field
• A track record of delivering results even when requirements are under-specified
• Experience building or using A/B testing infrastructure.
• Experience building ML tools and frameworks, analytics tools or data products
• A background in applied statistics with experience building systems at the boundary between data science and engineering.
At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A).