At Uber, they ignite opportunity by setting the world in motion. They take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.
They 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 them, and let’s move the world forward, together.
About The Role
Are you interested in working at the intersection of applied quantitative research, engineering development, and data science? Do you have an interest in developing and applying quantitative solutions uniquely challenging problems on Uber Eats? If so, then this is the job for you.
What You’ll Need
They are looking for people with advanced quantitative degrees who are comfortable enough with research methodologies that they can address abstract business and product problems with extreme precision, and who have the enthusiasm and initiative necessary to deliver those answers at Uber’s fast pace. You should also have demonstrable programming skills and be comfortable with the engineering development process.
- Must have 4+ years industry experience outside of academic or internship setting. Prior research, data science, engineering experience in the recommender system or information retrieval preferred
- Superb quantitative background (e.g. machine learning, statistics, computer science, etc.): Graduate degree required and PhD preferred
- 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
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 within the team:
[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 their 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: personalized restaurant and dish recommendation, search relevance and food knowledge platform, new user acquisition spend optimization, messaging and push notification relevance, search engine optimization (SEO) and search engine marketing (SEM),, appeasement and refund optimization, user conversion and churn modeling.
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1