Machine Learning Engineer

PayPal PayPal · Fintech · Chicago, IL +2 · Machine Learning Engineering

Machine Learning Engineer at PayPal focused on developing, validating, and deploying ML models for fraud detection, credit underwriting, and marketing analytics. The role involves ensuring data quality, collaborating with cross-functional teams, and adhering to model risk management and responsible AI principles within a regulated fintech environment.

What you'd actually do

  1. Assist in the development and optimization of machine learning models.
  2. Preprocess and analyze datasets to ensure data quality.
  3. Collaborate with senior engineers and data scientists on model deployment.
  4. Conduct experiments and run machine learning tests.
  5. Stay updated with the latest advancements in machine learning.

Skills

Required

  • Familiarity with ML frameworks like TensorFlow or scikit-learn
  • Strong analytical and problem-solving skills
  • Advanced knowledge of statistical and machine learning models (e.g., logistic regression, time series analysis, random forests, SVMs, XGBoost, CNNs/RNNs)
  • Advanced coding skills in dealing with big data (e.g., Scikit-learn in Python, Tensorflow, Hadoop, Spark, SQL, etc.)
  • Relevant Modeling experience in credit scoring, fraud detection, financial forecasting, or marketing analytics

Nice to have

  • An advanced degree in a quantitative field, such as statistics, mathematics, computer science or engineering

What the JD emphasized

  • Model Risk Management Policy
  • Responsible AI
  • regulatory expectation

Other signals

  • Develop and optimize machine learning models
  • Deploy models into production environments
  • Model validation
  • Responsible AI