Data Scientist - Intermediate
Summary
Validate AI/ML models for credit risk, marketing, and fraud using Python and GCP, while contributing to model risk policies and monitoring regulatory guidelines.
You will validate models across financial domains, automate workflows with GCP, execute AI validation projects, collaborate across departments, contribute to AI and model risk policies, and monitor industry practices and regulatory guidelines.
Responsibilities
- Validate models across consumer and commercial credit risk, marketing, fraud, and account management
- Use GCP to automate workflows and improve process integration
- Execute AI validation projects
- Collaborate with departments and stakeholders
- Contribute to AI practice and model risk management policies
- Monitor industry best practices and regulatory guidelines
Requirements
- 2–5 years of experience developing or validating models
- Master's degree or higher in Statistics, Mathematics, Engineering, Economics, Data Science, or a relevant discipline
- Expertise in machine learning, natural language processing, and deep learning
- Experience with Scikit-learn, StatsModels, or TensorFlow
- Advanced Python and SQL programming
- Strong interpersonal and collaboration skills
- Experience collaborating across geographies and organizational levels
- Knowledge of credit risk, marketing, or fraud models
Benefits
- Hybrid work setting
- Healthcare packages
- Paid time off