About CAS
The Core Analytics & Science Team (CAS) is Uber's largest data and applied sciences organization, covering both of Uber's main lines of business as well as the underlying platform technologies that power those businesses. We are a key part of Uber's cross-functional product development teams, helping to drive every stage of product development through data analytic, statistical, and algorithmic expertise.
Product, Statistics, & Experimentation Applied Science
Here are some of the teams that make it happen:

• Platforms: Develops the common systems and technical foundations that power Uber's core trip experience (e.g., pickup/dropoff, time prediction, route selection, navigation), post-trip customer support and business reporting. Also develops novel experimental design and statistical models that power the company-wide experimentation platform.
• Mapping platform - We use extensively statistical, optimization, and machine learning models to perform travel time prediction, route optimization, navigation, and pickup and dropoff specification for both Rides and Eats.
• Experimentation - Build the experimentation platform at Uber, providing reliable, trustworthy and agile experimentation and experiment analysis to power business decisions across the entire Uber ecosystem

• Eats: Uber Eats is Uber's ambitious and rapidly expanding on-demand food delivery business currently operating in more than 45 countries globally and is the largest outside of China.
• Merchants - Optimizing merchant onboarding, menu creation, marketing, and order experience
• Couriers - Creating a stress-free courier experience at every point in their lifecycle
• Eaters - Building intelligent data-driven products to provide the best experience across new user acquisition, existing user engagement, and churned user resurrection

• Rides: Rides Data and Applied Sciences at Uber uses data to improve and automate all aspects of Uber's core ridesharing products.
• Shared Rides - Optimizing the balance between UberPool rider experience and cost
• Incentives, Subscriptions and Rewards - Design incentives, subscriptions and rewards programs for riders
• High Capacity Vehicles (aka Uber Bus) - Using movement data to predict demand and design optimized r

What You'll Do

• Develop creative solutions and build prototypes to business problems using algorithms based on machine learning, statistics, and optimization, and work with engineering/product to productionize those algorithms and create impact in production.
• Drive clarity and solve ambiguous, challenging business problems using data-driven approaches.
• Propose and guide the framework of data analysis to drive business insight and facilitate decisions. Establish standard methodologies for data science including modeling, coding, analytics, and experimentation.
• Leverage data to understand product performance and to identify improvement opportunities
• Design product experiments and interpret the results to draw detailed and impactful conclusions
• Communicate with senior management and multi-functional teams
• Provide recommendations to assist quick product ideation and feature launch decisions.
• Build intelligent data-driven products to provide the best user experience

Basic Qualifications

• Ph.D., MS or Bachelors degree in, Statistics, Economics, Machine Learning, Operations Research, Computer Science or other quantitative field. (If M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years of industry experience required)

• Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
• Knowledge of experimental design and analysis
• Experience with exploratory data analysis, statistical analysis and testing, and model development
• Ability to use a language like Python or R to work efficiently at scale with large data sets
• Proficiency in languages and tools like SQL, Hive, and Spark

Preferred Qualifications

• 5+ years of industry experience working as an applied scientist or similar
• Tech lead experience is a plus
• Experience with productionizing algorithms for real-time systems
• Proficiency in Java, Scala, or Go

• Advanced experience in experimental design and analysis (e.g., A/B and market-level experiments), as well as causal inference