2020 PhD University Graduate - Data Scientist - Uber Eats (New York)
Data Science, University en New York, NY
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.
About the Role
Uber Everything Data Scientists help solve the most challenging problems related to Uber's ambitious and rapidly expanding on-demand delivery businesses such as Uber Eats. Come tackle fascinating and difficult problems associated with Uber's three-sided delivery marketplace, including personalized search and recommendation for restaurants and dishes, travel and food preparation time prediction, text mining and natural language processing, demand and supply forecasting, growth and spend optimization, dynamic pricing, dispatch and routing optimization, and many more. To solve these problems, data scientists leverage unique data sources diverse in both geographical and temporal dimensions and in both structured (data from app sessions, trips, etc.) and unstructured (menu descriptions, food photos, support contacts, etc.) forms.
What You’ll Need
Graduate degree required with PhD preferred(with anticipated graduation in fall 2019 - spring 2020) in statistics, math, machine learning, operations research, economics, EECS, etc.
Prior research, data science modeling, or engineering experience in the aforementioned domains
Familiarity with technical tools for analysis - Python (with Pandas, etc.), R, SQL, etc.; previous software engineering background a plus
Research mindset with bias towards action - able to structure a project from idea to experimentation to prototype to implementation
Passionate and attentive self-starters, great communicators, amazing follow-through - you have a great work ethic and love the responsibility of being held accountable for the results
Bonus Points For
Experience with A/B testing
About the Team
Uber Eats Data Scientists help solve the most challenging problems related to Uber's ambitious and rapidly expanding on-demand food delivery businesses, which currently operates in more than 45 countries globally and is the largest outside of China. These fascinating and difficult problems include personalized search and recommendation for restaurants and dishes, travel and food preparation time prediction, text mining and natural language processing, demand and supply forecasting, growth and spend optimization, dynamic pricing, dispatch and routing optimization, and many more.
Below is a list of sub domains in our NYC location:
Restaurant (NYC) | The restaurant team aims to increase restaurant selection on Uber Eats while setting up restaurant partners for success. We leverage statistics and machine learning techniques to optimize the experience of restaurants at different life cycles. From onboarding, to menu creation, marketing, and order experience, we empower them with tools to increase demand and maintain a frictionless interaction with the platform.
Marketplace - Logistics and Marketplace Intelligence (NYC) | From dispatch and routing optimization to predicting food delivery time, the Logistics and & MI team provides DS solutions to create the best customer experience on all sides of the Eats marketplace in the most efficient way. The team also provides marketplace management solutions using state of the art machine learning techniques and our dispatch simulator.
En Uber no solo aceptamos la diferencia; la celebramos, la apoyamos y la valoramos para beneficio de nuestros empleados, de nuestros productos y de nuestra comunidad. Uber se enorgullece de ser un lugar de trabajo con igualdad de oportunidades y es un empleador de acción afirmativa. También estamos comprometidos con el empleo en igualdad de oportunidades sin considerar raza, color, origen familiar, religión, sexo, origen nacional, orientación sexual, edad, ciudadanía, estado civil, condición de discapacidad, identidad de género o estado de Veterano.