Sr Data Scientist

PayPal PayPal · Fintech · Chicago, IL +1 · Data Science

Senior Data Scientist at PayPal in Chicago, IL, focused on developing and implementing advanced data science models to address business problems and support the growth of PayPal's SMB portfolio. The role involves extracting and analyzing data, optimizing risk strategies through sensitivity and A/B testing, and communicating insights to stakeholders. Requires experience with SQL, Python, cloud systems (AWS/BigQuery), data visualization (Tableau), end-to-end ML model development (XGBoost, Random Forest, regression), business rule analysis, and fraud/credit risk.

What you'd actually do

  1. Lead the development and implementation of advanced data science models.
  2. Extract, analyze, and transform data into tactical and strategic insights that address business problems and support the profitable growth of PayPal’s Small and Medium-sized Business (SMB) portfolio using experience with regulatory frameworks related to SMB acquisitions.
  3. Identify key business levers, establish cause-and-effect relationships, and effectively communicate insights to stakeholders to drive data-informed decisions.
  4. Continuously extract and analyze credit exposure data, and conduct sensitivity and A/B testing sequences to optimize risk strategies.
  5. Design visually engaging data outputs in a clear and digestible format for business leads to review.

Skills

Required

  • SQL
  • Python
  • Pandas
  • NumPy
  • AWS
  • Google BigQuery
  • Tableau
  • XGBoost
  • Random forest
  • regression model
  • business rule analysis
  • fraud and credit risk
  • risk assessment methodologies
  • mitigation strategies

Nice to have

  • data analysis
  • data exploration
  • descriptive statistics
  • predictive modelling
  • data visualizations
  • reporting
  • decision engine

What the JD emphasized

  • regulatory frameworks related to SMB acquisitions
  • fraud and credit risk

Other signals

  • Develop and implement advanced data science models
  • Extract, analyze, and transform data into tactical and strategic insights
  • Optimize risk strategies
  • End-to-end machine learning model development process