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  • ID
    #52650991
  • Salary
    TBD
  • Source
    Uber
  • Date
    2024-10-06
  • Deadline
    2024-12-04
 
Full-time

About the RoleThe Driver Pricing team develops the algorithms, signals, and insights that power Uber's real-time driver pricing. We use elements of modeling, causal inference, and optimization to set driver prices that dynamically align both customers' and partners' interests while maximizing the value created by the marketplace.We are looking for experienced candidates with a passion for solving new and difficult problems with data. As a Staff Scientist, you will use strong quantitative skills in the fields of statistics, economics, machine learning, and operations research to improve real-time driver pricing. You will work with product managers and engineers on model development, experiment design, and pricing innovations. What the Candidate Will Do

Build statistical, optimization, and machine learning models for strategic insights, simulations, and deeper understanding of marketplace performance

Leverage large and sophisticated datasets to derive proactive insights that inform strategic decisions and improvements in key revenue-generating optimization engines at Uber

Design and implement pricing experiments and interpret the results to draw detailed and actionable conclusions

Present findings to senior management to advise on business decisions

Work closely with multi-functional leads and partner teams to develop technical vision, new methodological approaches, and drive team direction

Collaborate with product and engineering to drive pricing improvements end-to-end from conceptualization to final product

Basic Qualifications

Ph.D. or M.S. in Statistics, Economics, Mathematics, Operations Research, Machine Learning, or other related quantitative fields

6+ years of industry experience as an Applied Scientist, Data Scientist, or equivalent

Strong programming skills to prototype models and perform statistical analysis in Python (preferably), R, or similar

Proficiency in using Python, SQL, or similar technologies to work efficiently with large data sets

Experience in experimental design and analysis

Knowledge of underlying mathematical foundations of statistics, economics, machine learning, optimization, and analytics

Experience with exploratory data analysis, statistical analysis and testing, and model development

Preferred Qualifications

Experience leading complex technical projects and substantially influencing the scope and output of others

Track record of effectively engaging senior leadership and partner teams to build understanding of and consensus for the viewpoints of the team

Thought leadership to drive multi-functional projects across multiple teams from concept to production

Excellent communication skills to lead initiatives across multiple product areas and communicate findings with senior leadership

Experience of working with large dataset using Spark, Hive, and HDFS

For New York, NY-based roles: The base salary range for this role is USD$203,000 per year - USD$225,500 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$203,000 per year - USD$225,500 per year. For Seattle, WA-based roles: The base salary range for this role is USD$203,000 per year - USD$225,500 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.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 this form- https://docs.google.com/forms/d/e/1FAIpQLSdbY9Bv8-lWDMbpidF2GKXsxzNh11wUUVS7fM1znOfEJsVeA/viewform

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