Data Scientist II, Tech

Uber·Oracle Recruiting
Sunnyvale, CAFull-time$174k–$209kPosted Jun 19, 2026
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Employer:                    Uber Technologies, Inc.  

Job Title:                      Data Scientist II, Tech 

 

Job Location:              Sunnyvale, California

Job Type:                     Full Time

Rate of Pay:                 $174,304 to $209,164 per Year

You will be eligible to participate in Uber's bonus program, and may be offered 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.

Duties:                         Perform statistical analyses to understand risk and fraud behaviors and contribute to the development of fraud detection features and models. Build and maintain fraud rules in response to evolving fraud behaviors. Extract insights from large volumes of data to formulate new strategies for mitigating or stopping fraudulent activities. Develop a deep understanding of risk data, reporting, and key metrics. Conduct experiments to test and optimize the effectiveness of risk mitigation products and solutions. Participate in project definition and collaborative initiatives with global stakeholders focused on risk and fraud mitigation. Present findings effectively to the management team to support business decision-making. With guidance, define and develop a specific area of expertise. Stay engaged and proactive, as the environment is fast-paced. May telecommute.

Employer will accept a Master's degree in Mathematics, Statistics, Computer Science, Operational Research, Economics, or a related field and 2 years of experience in the job offered or in a related occupation.

 

Position requires:

  1. R or Python;
  2. Database query languages: SQL;
  3. Experimentation techniques including simulation or A/B testing;
  4. Statistical analysis including descriptive statistics, correlation, regression, or confidence intervals;
  5. Developing relevant metrics;
  6. KPIs to measure performance by product teams;
  7. Quantitative modeling including machine learning models, time-series forecasting, or casual impact analyses;
  8. Experience in risk, fraud, or payments.
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