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Staff Data Scientist - Risk and Payments

Data Science
in San Francisco, California

About the Role

We are looking for a staff / leadership team level individual contributor data scientist who will help raise the bar for technical and statistical rigor across our combined Risk & Payments data science and analytics organization. You will be part of the leadership team for a ~100 person data org and will be charged with (1) diving deep into our thorniest and most complex causal inference and machine learning problems; and (2) acting as a technical mentor to our top data science talent from across the Risk & Payments organization.

What You'll Need

  • Excellent educational background in machine learning, statistics, applied math, economics, operations research, or a related field. Masters or PhD degree preferred.
  • At least 6 years industry experience in time series modeling or machine learning, with significant personal experience as a technical contributor. Experience working with large data sets; experience with spatial data a plus.
  • Recognition as a global leader in at least two data science specialties (i.e. causal inference techniques, deep learning, NLP, recommender systems, etc.)
  • Some experience as a technical mentor / coach. You will not have formal management responsibilities but will be expected to act as a technical mentor to several senior data scientists.
  • Entrepreneurial mindset. Everywhere you go, you can't help but mobilize people, create things, solve problems, roll up your sleeves, collaborate, go above and beyond. You are an insatiable doer and motivator of others.
  • Excellent execution and organization. This team will be working with engineers and product leads at the forefront of the development cycle. To excel in this role, you should be comfortable executing with little oversight and be able to adapt to problems quickly.
  • Experience with common analysis tools - Python, R, and SQL. Demonstrable familiarity with code and programming concepts.

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 600 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.