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2019 University Graduate - Data Scientist - UberEats

Data Science, University in San Francisco, California

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 2019) 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 San Francisco location:

  • Eater (SF) | From new user acquisition, to existing user engagement, to churned user resurrection, the eater team builds intelligent data-driven products to provide the best user experience. The Eater team is responsible for shaping the business with our expertise in machine learning (including learning to rank, deep learning and NLP), optimization, causal inference, statistics, and a passion for connecting everyone with their favorite food. The challenges the Eater team tackles include: New user acquisition spend optimization, messaging and push notification relevance, search engine optimization (SEO) and search engine marketing (SEM), personalized restaurant and dish recommendation, search relevance and food knowledge platform, appeasement and refund optimization, user conversion and churn modeling.
  • Courier (SF) | We strive to create a stress free courier experience at every point in their lifecycle, down to the nuances of individual deliveries. We utilize machine learning and statistical techniques to optimize courier onboarding, the on-trip experience, further our understanding of how couriers move within and across a city, and power the models to guide our couriers on how to plan their day and increase their earnings potential. Through our segmentation and marketing efforts, we are also building out our one-of-a-kind loyalty program, to recognize and reward couriers for their commitment and quality of service. We continually optimize for retainment and engagement of our partners.
  • Marketplace - Pricing (SF) | The pricing team develops algorithms to find the perfect price every time an eater or courier makes a decision. For eaters, we design structural delivery fees, targeted promotions, and real-time reliability pricing. For couriers, we design engagement incentives, positioning incentives, real-time surge, and trip-level pricing. The pricing team uses elements of modeling, causal inference, forecasting, and optimization to design prices that dynamically align customer's and partner's interests with maximizing value created by the marketplace.

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.