2019 University Graduate - Data Scientist - Driver Compliance Uber
Seattle, WA

Job Description

Uber Overview

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.

Job Description

About the Role

The Driver team at Uber is focused on accelerating driver growth, engagement, and retention across 300+ cities worldwide. Data Scientists on Driver play a central role in guiding product development and strategy through the discovery of insights from data. In this position, you will offer a data-driven perspective and work closely with product, engineering, and marketing. You will be on the forefront of analysis and leverage our data sources to propose new ideas related to every area of our product, including developing predictive models of driver behavior, studying market balance and developing a growth model in the context of a two-sided market, creating experiment designs for product changes with difficult constraints (e.g. extensive product network effects). Our team's autonomy gives us the flexibility to focus on the highest-impact projects in this adaptive and challenging role as we bring increasing numbers of riders and drivers onto the Uber platform.

The Driver Compliance Data Science team is based out of Seattle and falls into the greater Driver org. The charter of the Driver Compliance team is to ensure that all rides on the platform are completed by drivers who meet all the necessary compliance requirements at the time of a trip and to ensure that Drivers have all the best tools possible to remain compliant at all times. Duties in Driver Compliance DS team cross the entire DS space including inference, data engineering, machine learning, economics, optimization, experiment, business intelligence, customer intelligence, and data visualization.

What You'll Do / What You'll Need / Bonus Points / About the Team What You'll Do

* Leverage data to perform intensive analysis across all areas of our business to catalyze product development
* Apply economics, optimization and machine learning techniques to solve incentives, scheduling, and other real-world complex problems
* Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess the relative impact and extract trends
* Design experiments and interpret the results to draw detailed and actionable conclusions
* Create models to enhance understanding of user behavior and predict future performance of cohorts
* Generate and execute on ideas for exploratory analysis to shape future projects and provide recommendations for actions
* Define KPIs, create dashboards and reports to regularly communicate results by building data pipeline and monitoring data quality
* Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing

What You'll Need

* Masters or PhD (with anticipated graduation in 2019) in Economics, Operation Research, Statistics, Computer Science, Physics, or other quantitative fields
* Ability to write code and contribute to a code base in Python or R
* Experience writing and understanding complex SQL; experience working with large datasets
* Experience in experimentation - A/B, sequential and multi-armed bandit, practical A/B testing experience preferred
* Good understanding of machine learning and statistical modeling
* Collaborate closely with cross-functional teams to execute on decisions
* Excellent communication and presentation skills