Senior Scientist, Earner Experience
Uber
New York, New York
Posted 1 weeks ago
Qualifications
Education
Ph.D., M.S., or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields.
Responsibilities
Primary Duties
- Use data to understand product performance and to identify improvement opportunities.
- Develop novel experimentation and/or measurement methodology for use in large-scale marketplace settings.
- Design and execute product experiments and interpret the results to draw detailed and actionable conclusions.
- Present findings to inform business decisions.
- Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization.
Experience Requirements
Required
Minimum 4 years of industry or academic experience as an Applied or Data Scientist or equivalent (with at least two of those years in industry).
4 years of experience
Benefits & Perks
Benefits Package
- 401(k) plan
- various benefits
Required Skills
Technical Skills
PythonRSQL
Full Job Description
Senior Scientist, Earner Experience
Data Scientist, Data Science in New York, New York - Full Time
About the Role
The Earner org is responsible for the products and programs that make earning through the Uber marketplace a rewarding experience. As a Scientist, you will leverage your expertise in economics, operations, machine learning, and statistical modeling to improve the efficiency of our platform and help direct the development of our products. This role will have a particular focus on offer decision making and preferences.
What the Candidate Will Do
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity 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 this form.
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.
Data Scientist, Data Science in New York, New York - Full Time
About the Role
The Earner org is responsible for the products and programs that make earning through the Uber marketplace a rewarding experience. As a Scientist, you will leverage your expertise in economics, operations, machine learning, and statistical modeling to improve the efficiency of our platform and help direct the development of our products. This role will have a particular focus on offer decision making and preferences.
What the Candidate Will Do
- Use data to understand product performance and to identify improvement opportunities.
- Develop novel experimentation and/or measurement methodology for use in large-scale marketplace settings.
- Design and execute product experiments and interpret the results to draw detailed and actionable conclusions.
- Present findings to inform business decisions.
- Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization.
- Ph.D., M.S., or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields.
- Minimum 4 years of industry or academic experience as an Applied or Data Scientist or equivalent (with at least two of those years in industry).
- Experience in experimental design and analysis.
- Experience with exploratory data analysis, statistical analysis and testing, and model development.
- Proficiency in Python/R and SQL.
- Minimum 6 years of industry/tech experience in applied science, data science, economics, machine learning, and/or optimization roles.
- Experience in using Python to work efficiently at scale with large data sets.
- Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics.
- Experience in algorithm development and prototyping.
- Experience in pricing optimization and/or marketplace design.
- Experience in designing large scale experiments in complex environments.
- Well-honed communication and presentation skills.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity 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 this form.
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.





