Skip to main content

Tell us your location

Please enter your nearest city name to help us display the correct information for your area

Select your language

Data Science Manager, Uber AI

undefined, Data Science in San Francisco, CA

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 Team

The AI org at Uber is a pillar of excellence in the fields of artificial intelligence and machine learning. To ensure that their innovations are materialized at Uber, we staff an exceptional data scientist team to build applied products that leverage the research learnings. The three primary areas of investment for the data science team are computer vision, conversational AI (primarily NLP/NLU), and sensing & perception. The team develops offline prototypes with researchers to demonstrate value, productionizes scalable models in conjunction with engineers, and designs rigorous experiments in collaboration with product managers’ vision.


We are looking for data science/engineering leader to direct this team through both technical guidance and stakeholder management. The ideal manager will be able to converse with the team about nuanced machine learning concepts, but also capable of translating requirements and setting expectations with all of the teams we partner with across the company.

What You'll Do

  • Horserace deep learning architectures (e.g., CNN, LSTM, GRU) to develop the most accurate NLP models for labeling and routing support tickets (link, link)
  • Develop computer vision solutions to augment our OCR technology
  • Design novel methodologies for evaluating the stability of neural-network based embeddings
  • Visualize and simplify the way Uber communicates via support by using topic modeling and various unsupervised algorithms
  • Train deep learning models to enable one-click responses between riders and drivers (link)
  • Partner with our infrastructure teams to test and iterate on new cutting-edge ML software (link, link)


What You'll Need

  • A graduate degree (MS or PhD) or equivalent in statistics, machine learning, computer science, or a quantitative domain.
  • 3+ years professional experience as an individual contributor delivering highly successful and innovative machine learning products
  • 3+ years experience managing a team of at least 4 engineers or data scientists as well as leading large scale ML projects to production
  • You bring substantial depth in at least 1-2 ML specialities (i.e. NLP, CV, active learning, etc) where you can teach/develop others
  • Stellar communication skills - Capable of both explaining complex concepts to stakeholders as well as coaching technical individuals on their approaches. In short, you can speak both academic and business languages to ensure both technical accuracy while still prioritizing impact.
  • Collaborative and organized execution - This team will be working with engineers, product leads and researchers at the forefront of the development cycle. To excel in this role you will need to work to understand your customer, disambiguate requirements, and openly navigate roadblocks to deliver ML solutions within started timelines.
  • A commitment to learning - We want someone who seeks to deliver impact, but also invests in themselves and their team. You will help craft development and career plans for folks seeking to grow their technical and softer skills.

See our Candidate Privacy Statement

At Uber we don’t just accept difference—we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.