Perform an in-depth technical review of models, evaluating aspects such as conceptual soundness, appropriateness of model methodologies, data quality, and model implementation;
Conduct independent validation and testing of a range of GenAI and other models across various global business lines and locations to identify vulnerabilities and potential business risks;
Ensure model compliance with regulations, internal policies, and industry best practices;
Collaborate closely with cross-functional teams, including model developers, risk managers, and stakeholders, to address findings related to the models and promote best practices;
Stay updated on industry trends and regulatory guidelines, particularly those related to generative AI and advanced analytical models, to contribute to the continuous improvement of validation methodologies, standards and automation.
Requirements:
Completed higher education in econometrics/quantitative finance/quantitative methods/mathematics/statistics/physics;
In-depth knowledge of deep learning generative AI techniques, particularly Large Language Models and their widespread applications.
Strong expertise in traditional machine learning methods, including supervised and unsupervised learning, classification, regression, clustering, and text mining.
Min. 4 years of professional experience in validation or development of machine learning models in a financial institution or related industry;
Analytical skills with the ability to critically assess complex models, effectively articulate and document model risk findings;
Experience writing code in Python/ R/ SAS or other statistical programming language;
Fluent English (min. C1).
Offer:
Ability to work in the hybrid model;
Stable employment;
Flexible working hours;
Daily work using English in an international environment;
Participation in interesting, strategic projects;
Opportunity to obtain additional professional training;
An attractive package of benefits (medical care, insurance, use of the corporate gym, relaxation zone).
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