Data Scientist Ii, Tech

Uber Uber · Consumer · Sunnyvale, CA · Data Science

Develop and maintain fraud detection features and models, extract insights from data to mitigate fraud, and conduct experiments to optimize risk mitigation solutions. Requires experience in risk, fraud, or payments, and proficiency in Python/R, SQL, experimentation, statistical analysis, and quantitative modeling including machine learning.

What you'd actually do

  1. Perform statistical analyses to understand risk and fraud behaviors and contribute to the development of fraud detection features and models.
  2. Build and maintain fraud rules in response to evolving fraud behaviors.
  3. Extract insights from large volumes of data to formulate new strategies for mitigating or stopping fraudulent activities.
  4. Develop a deep understanding of risk data, reporting, and key metrics.
  5. Conduct experiments to test and optimize the effectiveness of risk mitigation products and solutions.

Skills

Required

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

What the JD emphasized

  • fraud detection features and models
  • risk and fraud mitigation
  • machine learning models

Other signals

  • fraud detection models
  • risk and fraud mitigation
  • machine learning models