As a data scientist, you will build predictive models using supervised and unsupervised methods to analyze fraud behavior based on historical risk and expert experience. Your key responsibility will be to work closely with risk strategy analysts in solving real business problems using appropriate algorithms.
Key Responsibilities
Design and implement optimal risk-benefit decisions by leveraging optimization techniques and methods.
Collaborate with cross-functional teams to develop and deploy machine learning models that drive business outcomes.
Analyze large datasets to identify trends and patterns that inform risk mitigation strategies.
Requirements
A PhD or Master's degree in Computer Science, Statistics, or a related field.
Solid understanding of machine learning algorithms and tools like SQL and Python.
Adept analytical thinking and problem-solving skills.
Self-motivated with excellent communication skills.
Benefits
Opportunity to work on complex business problems and develop innovative solutions.
Collaborative and dynamic work environment.
Professional growth and development opportunities.
Data Scientist - Predictive Modeling and Risk Analysis is a challenging yet rewarding role for professionals who enjoy working with data and developing predictive models to mitigate risk.