Data Scientist – Banking and Risk Management
Job Description:
Data Scientist – Banking and Risk Management
Role Summary:
The Data Scientists will design AI/ML models for banking and risk management, driving innovation and
enhancing operational efficiencies for financial institutions.
Key Responsibilities:
Develop AI/ML models for credit scoring, fraud detection, and risk assessment in banking.
Analyze large datasets from banking systems to identify risk trends and insights.
Build predictive analytics solutions for portfolio performance and default probabilities.
Integrate AI/ML solutions into risk management frameworks for regulatory reporting.
Collaborate with financial institutions to optimize risk strategies using advanced data science
tools.
Required Skills:
Proficiency in Python, R, and machine learning frameworks (TensorFlow, PyTorch).
Knowledge of banking risk metrics and regulatory requirements (e.g., Basel, IFRS 9).
Experience with financial data analysis and visualization tools (e.g., Tableau, Power BI).
Bachelor’s/Master’s in Data Science, Computer Science, or Financial Technology.
Strong understanding of banking processes and risk management practices.
Key Skills :
Company Profile
Is the American member firm of --- Thornton International, the seventh largest accounting network in the world by combined fee income.
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