Job Summary
The role involves analyzing extensive datasets to uncover fraudulent behavior and creating machine learning algorithms for detecting fraud across numerous risk areas. You will work closely with engineering teams to implement these models into a production environment and oversee their performance and the quality of features used.
Responsibilities
- Examine large datasets to pinpoint patterns associated with fraud.
- Develop machine learning models aimed at fraud detection across different risk sectors.
- Partner with engineering teams for the deployment of models into production.
- Monitor and assess the performance and quality of features within the deployed models.
Qualifications
- Minimum of 5 years of experience in the fields of data science or machine learning.
- Strong experience with fraud detection or risk modeling.
- Bachelor’s or advanced degree in a quantitative discipline.
- Proficient in programming with Python and using PySpark.
Experian provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
