In a data-driven world, our data science and analytics team navigates the fastest route to accelerate our business. Taking numbers, statistics, and digital metrics and transforming them into actionable insights, we utilize machine learning, AI, natural language processing, and advanced statistical modeling to implement automations and algorithms that enhance safety, amplify performance, improve our customer experience across Uber, and make magic in the marketplace.
Inside Data Science & Analytics
Where data science, law, and economics meet at Uber
Meet Juan Manuel Contreras, Ph.D., a cognitive neuroscientist turned data science manager at Uber. Juan Manuel works at the intersection of data science, law, and economics to help drive Uber’s legal and business strategies.
How applied and data science leader is driving innovation at Uber Freight
Minji leads the Applied and Data Science team for Pricing at Uber Freight. She gives us a behind-the-scenes look at her career so far, the lessons she’s learned, and what continues to excite her.
At Uber we’re reimagining the way the world moves for the better. We are helping people go anywhere and get anything. And we do it on a global scale, at the speed of now.
Our Return to the Office
It’s still early days as we look to find the right long-term model for Uber, yet we want this to continue being a great place for our current and future employees, and that means adapting to different needs. Our hybrid work approach focuses on increased flexibility.
Explore our Data Science teams
Safety & Insurance
The Safety and Insurance Data Science and Analytics team specializes in rare events. The team works closely with stakeholders across Product, Engineering, Operations, Marketing, and Legal to build new product features, implement machine learning algorithms, and optimize safety policies to help reduce safety incidents and make safer for riders, driver, eaters, restaurants, and all people who use Uber’s platform.
The Rides Data Science team uses data to improve and automate all aspects of Uber’s core ridesharing products. Key subteams include Driver, Forecasting, Global Intelligence, Maps, Marketplace Controls, Matching, Pricing/Loyalty, Rider, and Uber for Business.
Risk Data Science and Analytics teams provide insights and develop machine learning models and strategies to combat payment fraud and marketplace abuse, improve account security and integrity, and minimize credit risk for financial products.
Uber Eats Data Scientists help solve the most challenging problems related to Uber's ambitious and rapidly expanding Uber Eats business. These fascinating and difficult problems include personalized search and recommendation for restaurants and dishes, travel and food preparation time prediction, text mining and natural language processing, demand and supply forecasting, growth and spend optimization, dynamic pricing, dispatch and routing optimization, and many more.
Our policy data scientists support our policy issue experts around the world, equipping them with data to support our public policy positions. The Economics team produces in-house research and collaborates with world-leading academics to understand our marketplace and improve our product.
The Platform Data Science team works at the intersection of data science and engineering. Domain experts develop and advance platforms, including the platforms for Forecasting, Experimentation, Anomaly Detection, Computer Vision, Conversational AI, Sensing and Perception, and City Platforms. We also are the Data Science and Analytics partners for Finance, Customer Obsession, Infrastructure, Growth Platform and Office of the CTO and provide Behavioral Science insights across Uber.
Marketing data science informs decisions across Uber’s global marketing efforts, accelerating both demand and supply growth worldwide. We leverage advanced statistical modeling, machine learning, or data mining techniques in a scalable manner including large scale data processing such as Spark, Hive, and Uber’s proprietary machine learning platform, and more.
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