Data Scientist - Machine Learning, Global Intelligence Uber
San Francisco, CA

Job Description

Uber Overview

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.

Job Description

About the Role

Are you interested in working at the intersection of AI & Applied Machine Learning, mathematical modeling, engineering, and scalable data computation? Do you have an interest in developing and applying quantitative scalable solutions related to Uber's challenging challenges? If so, then this is the job for you.

What You'll Do / What You'll Need / Bonus Points / About the Team

What you'll need

* 3+ years of experience in ML research, data science, or engineering in building and implementing machine learning models/algorithms, particularly around classification, segmentation, multivariate regression, pattern recognition, etc. Exposure/experience with deep learning and reinforcement learning is a plus.
* Excellent programming skills - ability to prototype effective simple or complex algorithms and collaborate with the engineering team to implement them in the production system.
* Solid data skills - ability to extract complex data from various data systems (HDFS, elastic search, etc.) and streamline the process.
* Strong quantitative background: PhDs preferred.

About the Team:

This team focuses on improving Uber network efficiency and leadership position in the category with better data and algorithms. The challenging problems include modeling the complex market-level dynamics, rider and driver choices, cross-service decision across rides/eats/bike, optimizing Uber's pricing with market-level signals, etc. The ML data scientists on the team leverage the massive amount of Uber internal and external data to address these challenges, build scalable solutions with the powerful Machine Learning platform and infrastructure (Spark/parallel computing, GPU, etc. ).

We are looking for people with advanced quantitative degrees who are comfortable enough with ML research and algorithms to tackle critical product and business problems, and who are enthusiastic about dealing with complicated structured/unstructured data. You should also have demonstrable programming skills and be comfortable with the engineering development process.