Sr Scientist - Mobility Matching Science

Uber

  • Toronto, ON
  • Permanent
  • Temps-plein
  • Il y a 1 mois
Have you ever wondered why it's taking so long for an earner to be matched to your trip, why the ETA is so long, or how an Earner is picked from the many around you? If so, the Mobility Matching Science team is for you!The Matching team at Uber builds the systems that determine the optimal way to fulfill trips on the Mobility platform. We work on the problems of determining which earners to send an offer to and when. The solutions we build are critical for maintaining reliability and ensuring the trust of riders and earners alike.We are looking for experienced scientists who relish the opportunity to develop novel approaches and apply them at Uber's scale. They ideally have a good balance of causal inference, analysis, experimentation, and modeling knowledge, as well as, an ability to use these skills to identify business opportunities and deliver product recommendations.What You'll Do
  • Develop data-driven business insights and work with cross-functional stakeholders to identify opportunities and recommend prioritization of product, growth and optimization initiatives
  • Design and analyze experiments, communicating results that draw detailed and actionable conclusions
  • Analyze and contribute to development of optimization algos and ML models for use in mobility matching
  • Collaborate with cross-functional teams such as product, engineering and operations to drive system development end-to-end from conceptualization to final product
Basic Qualifications
  • Ph.D., M.S. or Bachelor's degree in Statistics, Economics, Mathemathics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
  • Minimum 1 year of industry experience as an Applied or Data Scientist or equivalent.
  • Proficient in Python/R to able to work efficiently at scale with large datasets
  • Knowledge of experimental design and analysis (A/B, Switchbacks, Synthetic Control, Diff in Diff etc)
  • Experience with exploratory data analysis, statistical analysis and testing and model development
Preferred Qualifications
  • Ability to work in self-guided manner
  • Good communication skills across technical, non-technical and executive audiences
  • Have a growth mindset; love solving ambiguous, ambitious and impactful problems
  • Experience in optimization and/or algorithm development
  • Experience with dashboard / data visualization tools (i.e Tableau, Mixpanel, Looker or similar)
  • Experience working on online experiments
For Canada-based roles: The base salary range for this role is CAD$164,000 per year - CAD$182,000 per year.For San Francisco, CA-based roles: The base salary range for this role is USD$183,000 per year - USD$203,000 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 .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 .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 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, Veteran Status, or any other characteristic protected by law.

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