Ameriabank CJSC

ML validator in model risk

In short

This role validates, monitors, and improves machine learning models across a bank, ensuring data quality, reliability, explainability, and compliance with Model Risk Management (MRM) standards. The position requires a university degree in statistics, math, risk management or engineering, strong statistics/probability knowledge, Python experience (poetry, Git, Docker), and understanding of model interpretability and data/model drift. It's an onsite, full-time, middle-level position in Yerevan requiring fluent Armenian and English.

Description
The incumbent will be responsible for validating, monitoring, and improving machine learning models across the bank, ensuring data quality, model reliability, explainability, and compliance with Model Risk Management (MRM) standards.
Responsibilities
•Preparation and ensuring of data quality control measures for training and validation of machine learning models in different business processes of the bank
•Development of methods and principles for validation and testing of machine learning models in the bank
•Development of automated systems for machine learning micro services' validation
•Development and ensuring of model risk management process (MRM)
•Machine learning model quality monitoring systems' development
•Models' business analytics and validation methodology improvement
•Development of technical requirements for model validation components
•Model validation and quality control (explainability & interpretability) reporting and communication to stakeholders
•Recommendations for improvements of machine learning models' lifecycle system
•Carrying out other related tasks delegated by the manager
Requirements
•University degree in statistics, math modeling, mathematics, risk management or engineering
•Strong knowledge of statistics and probability, knowledge of financial analysis and machine learning models
•Understanding of interpretability analysis for statistical models (regression analysis, decision trees, gradient boosting etc.) and deep learning models
•Understanding the data drift, model drift and concept drift problems and how to deal with them
•Experience with Python development, including also poetry, Git, code review tools, pip and Docker
•Analytical and creative thinking
•Communication and team-player skills; cooperation and consultation skills
•Good command of Armenian and English
Nice to have
•Experience with SHAP and ELI5 frameworks
Conditions
No conditions specified in the posting.

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