About the Role
Are you interested in working at the intersection of machine learning (ML), engineering, and data science? Are you passionate about developing next-generation algorithms to power a variety of unique solutions in the recommendation, search and knowledge graph space? If so, then this is the job for you!
We are looking for a forward-thinking data science lead/manager in the SF office to own the challenging modeling and algorithmic development work in the Consumer (Eater) facing product area for Uber Eats.
What You’ll Do
- Lead and develop a group of data scientists to tackle impactful problems such as Recommendation, Search Relevance, Knowledge Graph, etc. Your efforts will critically impact the growth, efficiency, and reliability of Uber Eats’ marketplace.
- Comfortable enough with research methodologies to address abstract business and product problems with utmost precision.
- Your deep technical knowledge will allow you to work across data science, product and engineering teams working together to accomplish extremely ambitious goals and build a great product.
- Strong expertise in machine learning.
- Superb quantitative background (e.g. machine learning, statistics or computer science). Graduate degree required. Bias towards action and impact – able to structure a project from idea, prototyping, productionization to impact quantification. Industry experience with a proven track record of delivering impactful results preferred.
- Advanced quantitative degree (Master and above)
- Familiarity with technical tools including Tensorflow/PyTorch and Hive/Spark.
- Hardworking and attentive self-starter, great communicator, amazing follow-through – you have a great work ethic and love the responsibility of being held accountable for the results.
- Prior research or industry experience in the Recommender Systems (RecSys), Personalization, Search Relevance, Information Retrieval (IR), Deep Learning, Reinforcement Learning or Natural Language Processing (NLP) preferred.
- Prior management / team-lead experience. You’ll be leading several direct reports initially and will have the opportunity to build, scale and nourish a team of experienced professionals.
- Advanced quantitative degree (PhD)
- Previous software engineering background is a plus.
About the Team
Uber Eats is Uber’s ambitious and rapidly expanding on-demand food delivery business currently operating in more than 45 countries globally and is the largest outside of China. Applied Machine Learning Scientists in Uber Eats solve many exciting problems in the Recommendation, Search and Knowledge Graph space:
Recommendation: We help users discover the food they love through personalized recommendation, which jointly optimizes multiple objectives such as user engagement, restaurant demand, and long-term health of the marketplace.
Search: We help connect users with what they are looking for, let it be a cuisine, restaurant, or dish. We understand their intention and optimize their query, proactively suggest relevant search queries, build novel algorithms to power both search retrieval and ranking.
Knowledge Graph: To enhance the recommendation and search capabilities, we build an extensive knowledge graph to capture the relationship between food, restaurants, users and other marketplace entities using a wealth of data unique to Uber and Uber Eats.
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.
To apply for this job please visit www.uber.com.