Sr Staff Data Scientist - Core Services at Uber (San Francisco, CA)

| San Francisco, CA
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About the Role
Uber's Core Services team provides the innovations in safety, support, payments, and insurance to help all users experience a smooth ride or delivery on Uber's platform. In order to do this, our processes and services need to run efficiently!
We're looking for an experienced Sr Staff Data Scientist to work directly with the VP of Core Services to identify, investigate, and determine the root cause for issues which come up within the Core Services Platform. This senior role reports to the Head of Core Services Data Science.
Note on related roles:
While Data Scientists in this role may extend and apply machine learning or statistical models, if you're interested in a role focused on advanced modeling, please check out our Applied Science roles instead.
What the Candidate Will Do
  • Work closely with Uber's Core Services Product Managers, Engineers, and Operations Team to understand business and data relationships
  • Prioritize, through data, product or process areas needing investigation and analysis
  • Perform data analysis into issues impacting our users in order to find root cause
  • Work with Core Services leadership team to suggest path to remediate issues
Basic Qualifications
  • Bachelor's in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative field.
  • Experience with Data ETL, Data Profiling
  • Experience with SQL as well as distributed data variant such as HiveQL and PrestoSQL/Trino
  • Proficient with a scripting language, such Python or R, for data analysis
  • Minimum 8 years as a Data Scientist, Applied Scientist, Data Engineer or equivalent
Preferred Qualifications
  • Experience working with data to diagnose products and processes
  • Investigative, detail-oriented, and sharp - able to detect and find the root cause for anomalies, errors, or issues
  • Well-honed communication and presentation skills: able to transform a complex quantitative analysis into a succinct executive level reports
  • Experience in data engineering or log analysis a plus
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