Scientist I

About Th e Role

The Core Analytics & Science Team (CAS) is Uber's primary science organization, covering both our main lines of business as well as the underlying platform technologies on which those businesses are built. 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. CAS owns the experience and algorithms powering Uber's global Mobility and Delivery products. We optimize and personalize the rider experience, target incentives and introduce customizations for routing and matching for products and use cases that go beyond the core Uber capabilities.

About The Team

Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.

Within Uber, Earner Growth plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting.

Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience.

• What the Candidate Will Do ----
• Propose, design, and analyze large scale online experiments
• Define and implement metrics to measure product performance
• Develop innovative early life cycle products for new earners to increase their conversion
• Present findings to business and executive audiences
• Collaborate with engineers and product managers to implement ideas and plan future roadmaps
• Basic Qualifications ----
• MS degree in Economics, Operations Research, Statistics, Computer Science, or other quantitative field
• 1+ years of industry experience as an Applied or Data Scientist or equivalent
• Background in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl)
• Design experiments and interpret the results to draw detailed and actionable conclusions across a variety of key performance indicators
• Coding and SQL proficiency and ability to develop statistical analysis and algorithm prototyping in Python or R
• Ability to use Python, SQL, R or similar technologies to work efficiently with large data sets
• Experience working with cross-functional teams(product, science, product ops etc).
• Preferred Qualifications ----
• Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams
• Experience leading key technical projects and substantially influencing the scope and output of others
• Knowledge of experimental design and analysis or experience with exploratory data analysis and model development
• Experience communicating qualitative research methods and findings to non-qualitative researchers
• Track record of engaging senior leadership effectively to build understanding of and consensus for the viewpoints of the team
• Solid theoretical and applied ML skills and a strong background in mathematics and stats
• Solid Programming skills to prototype models in at least one of Python (preferably), R, Java, Go, Scala
• Expert in one of the following areas: A/B experimentation design, Causal Inference
• Experience of working with large dataset using Spark, Hive, HDFS is desired
• Analyze large data sets to identify behavior trends among good users and bad actors, using statistics, data mining, and machine learning techniques
• Thought leadership to drive multi-functional projects from concept to production.