About the Role
We are looking for Applied Scientists and Senior Applied Scientists for three teams: Customer Obsession, Risk, and Safety & Insurance.
Customer Obsession Applied Science is a group responsible for ensuring every Uber customer support experience is extraordinary. Specifically, this team works to build self-service technology and processes that are deeply integrated with the Uber customer support experience, making it easy for our customers and customer support representatives to get to the right outcome, faster. We are also responsible for building the models and algorithms that help Uber customers answer their own questions or, even better, avoid the need for a customer support experience at all.
Our Risk Applied Science team provides insights and develops machine learning models and strategies to combat payment fraud and marketplace abuse, improve account security and integrity, and minimize credit risk for financial products. Working in the risk domain is like playing an adversarial game with fraudsters: you will frequently work to identify new fraud patterns and provide scientific solutions to address emerging risk problems at scale.
The Safety and Insurance Applied Science team specializes in rare events. The team works closely with partners to build new product features, implement machine learning algorithms, and optimize safety policies to help reduce safety incidents and make it safer for riders, drivers, eaters, restaurants, and all people who use Uber's platform. This team pursues some of the hardest problems in all of Uber: improving the safety of cities and people all over the world. This position focuses on algorithmic solutions to understanding and improving interpersonal safety.
What You'll Do

• Develop and lead statistical and machine learning efforts in relation to your projects. Our projects use machine learning, experimentation, signal processing, time series analysis, geospatial analysis, natural language processing, and more. We'll give you as many challenges as you can seek and help you grow to tackle more.
• Use large scale data processing such as Spark, Hive, and Uber's proprietary machine learning platform, and more
• Collaborate with engineering to write and implement algorithms in production
• Work with a cross-functional team that includes product management, engineering, operations and others to execute on projects
• Drive transparency and seek ambiguous, meaningful business problems using data
• Propose and own data analysis (including modeling, coding, analytics, and experimentation) to drive business insight and facilitate decisions.
• A few recent problems involve building machine learning models to deliver contextual support content for eaters, riders, and earners by content recommendation; and; intelligent policy optimization.

Basic Qualifications

• Ph.D., M.S. or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields. (If M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 3+ years of industry experience as a Applied Scientist or equivalent)
• 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 like SQL, R, and Spark

Preferred Qualifications

• M.S. degree in Science, Engineering, or Mathematics fields and 3+ years of industry experience
• Ph.D. in Statistics, Machine Learning, Operations Research, or other quantitative field
• Experience in experimental design and analysis (e.g., A/B and market-level experiments)
• Experience with NLP is a plus.
• Experience in algorithm development and prototyping
• Experience with productionizing algorithms for real-time systems
• Proficiency in Java or Scala
• Passion for Uber!