About the Role Latin America Central Operations is the operational muscle that enables Uber's mobility business in the region, generating economic opportunities for over 3 million driversand helping more than 50 million monthly active riders reach their destinations. Data science needs to inform much of this work. From models to experiments, operations benefit from scientific precision and technical rigor. As a member of the Data Science team for the region, you will embed in an Operations team to design and deliver data science products that improve the scientific rigor and precision of your team's operational work. 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 and/or business performance and to identify improvement opportunities - Design 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. What you'll need: - 3 years of industry experience working as a Data Scientist or Data Analyst - Ph.D., M.S., or Bachelors degree in a quantitative field: Statistics, IT, Systems, Engeeniring - Knowledge of the mathematical foundations of statistics, machine learning, optimization, economics, analytics, and experimental design: A/B Testing - Experience with exploratory data analysis; statistical analysis and testing; and model development - Ability to use a language like Python to work efficiently at scale with large data - Proficiency in languages and tools like SQL, Hive, and Spark - Fluency in English, and fluency in either Spanish or Portuguese - Experience with productionizing algorithms for real-time systems - Advanced experience in experimental design and analysis (e.g., A/B and market-level experiments) as well as causal inference - Experience working in a fast-paced operations environment