Overview
On Site
Full Time
Skills
Distribution
Management
Business planning
Use cases
Customer experience
Expect
Algorithms
Statistics
Economics
Computer science
Machine Learning Operations (ML Ops)
SQL
Data
Communication
Leadership
Software development
Python
R
Java
User experience
Research
Pricing
Modeling
Design
Apache Spark
Apache Hive
HDFS
Law
Legal
Collaboration
Job Details
About the Role
Have you ever ordered food on Uber and when your order arrived wondered how it got to you so fast? Wondered where it came from and how much it would have cost Uber? If so, the Uber marketplace team is for you.
We build systems to look into the future and estimate the distribution of millions of orders worldwide and manage the demand on Uber Delivery marketplace. We build solutions that decide which restaurant is available at what distance at the right price. The tools we create are being sought after by diverse business planning use cases.
We are looking for an experienced scientist who relishes the opportunity to develop novel approaches and apply them at Uber's scale. Specifically, in this role, you will develop solutions to understand the customer experience and preferences on Uber platform to improve the Uber delivery experience as well as the overall marketplace performance.
What You'll Do
You will collaborate with other scientists, product managers, and business teams to understand the challenges in our space, then tackle problems that no one else has solved yet. We expect you to deliver end-to-end solutions rather than algorithms, and you will work closely with the engineers on the team to productionize, scale, and deploy your models world-wide.
Basic Qualifications4+ years of industry experience as an Applied or Data Scientist or equivalent.
Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.
Experience leading key technical projects and substantially influencing the scope and output of others.
Solid Programming skills to prototype models in at least one of Python (preferably), R, Java,
Expert in one of the following areas: (User Experience research methods, Pricing, Consumer Choice Modelling, A/B experimentation design, Causal Inference, or Mechanism Design)
Experience of working with large dataset using Spark, Hive, HDFS is desired
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing .
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing .
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
Have you ever ordered food on Uber and when your order arrived wondered how it got to you so fast? Wondered where it came from and how much it would have cost Uber? If so, the Uber marketplace team is for you.
We build systems to look into the future and estimate the distribution of millions of orders worldwide and manage the demand on Uber Delivery marketplace. We build solutions that decide which restaurant is available at what distance at the right price. The tools we create are being sought after by diverse business planning use cases.
We are looking for an experienced scientist who relishes the opportunity to develop novel approaches and apply them at Uber's scale. Specifically, in this role, you will develop solutions to understand the customer experience and preferences on Uber platform to improve the Uber delivery experience as well as the overall marketplace performance.
What You'll Do
You will collaborate with other scientists, product managers, and business teams to understand the challenges in our space, then tackle problems that no one else has solved yet. We expect you to deliver end-to-end solutions rather than algorithms, and you will work closely with the engineers on the team to productionize, scale, and deploy your models world-wide.
Basic Qualifications
- Ph.D., M.S. or Bachelor's degree in Statistics, Economics, Mathemathics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
- Ability to use Python, SQL, R or similar technologies to work efficiently with large data sets
- Design experiments and interpret the results to draw detailed and actionable conclusions across a variety of key performance indicators
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing .
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing .
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.