Data Scientist
- Джерело:
- djinni.co
Що робити
- Credit Risk Modeling: Develop portfolio risk models (PD, LGD, EAD) in line with IFRS 9 requirements;
- Income & Solvency Forecasting: Build ML models to assess customer financial condition based on transactional activity;
- Credit & Behavioral Scoring: Develop classical and advanced scoring systems for automated decision-making across the customer credit lifecycle;
- Market Risk Analysis: Apply time series analysis and ML techniques to assess liquidity risk, forecast FX volatility, and model customer fund behavior;
- Fraud & Anomaly Detection: Build and maintain systems for detecting unusual transaction patterns in real time;
Що пропонуємо
- Technology Stack: We use cloud solutions and modern development tools such as Amazon SageMaker, Amazon S3, Git, Confluence, etc.
- Scale: Working with large-scale datasets to support critical business decisions.
- Expertise: Risk models aligned with international standards and regulatory requirements.
- Professional Community: Strong Data Science community, regular internal workshops, participation in conferences, and sponsored learning.
- Automation: Proprietary system for managing the full ML lifecycle (from development to monitoring).
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