Data Scientist - Fraud Prevention

What role you will play in team: Develop and improve machine learning models for fraud detection and prevention within PayPal's ecosystem.

What you will do: Utilize statistical modeling and machine learning techniques to identify and mitigate fraudulent transactions.

Key responsibility:

• Develop and deploy machine learning models for fraud detection.
• Analyze large datasets of transactional data to identify patterns and anomalies.
• Evaluate model performance and make improvements as needed.
• 
  Collaborate with engineers and product managers.
• Stay up-to-date with the latest advancements in fraud detection techniques.

Required Qualification and Skills:

• Master's degree in Statistics, Computer Science, or a related field.
• 2+ years of experience in data science or machine learning.
• Proficiency in Python or R.
• Experience with machine learning libraries such as scikit-learn, XGBoost, or TensorFlow.
• Strong understanding of statistical modeling and machine learning techniques.

  Looking to get Placed? Try our Placement Guarantee Plan

  Get Hired

Benefits Included:

• Competitive salary and benefits package.
• Opportunities for professional development and growth.
• Impactful work in a dynamic and fast-paced environment.
• Opportunity to work on challenging problems with real-world impact.

A Day in the Life: A day would involve model training, performance analysis, algorithm optimization and collaboration with engineers and product managers.