Functieomschrijving
Job Tasks:Keep track of academic, industry, and internal developments in AI tools, methods, and practices to support a proactive agenda addressing emerging risks and challenges for ERM, ensuring MRM’s AI approach remains effective, efficient, and up to date Perform AI-related model validation activities in line with the Global Model Risk Policy, including reviewing model inputs, calculations, reporting outputs, conceptual soundness of underlying theory, suitability for intended use, and the relevance and completeness of data, qualitative information, and assumptions, as well as documentation and model implementation Identify opportunities to leverage AI tools and techniques to enhance internal MRM processes Assist in adapting or refining existing AI tools to facilitate their application in internal MRM processes Produce written validation reports summarizing findings and highlighting any issues discovered during the review Support the validation of remediation actions carried out by the ILOD to ensure appropriate resolution of identified concerns Contribute to the implementation of new Global Model Risk Policies and Procedures Provide assurance to model users, model owners, senior management, auditors, and regulators (across 1LOD, 2LOD, and 3LOD) that models and tools developed, maintained, and utilized within the organization comply with internal and regulatory standards and are suitable for their intended purposes Help strengthen management, regulatory, and external confidence in all models deployed across the organization
Requirements: Master’s or PhD degree in a quantitative field such as Science, Engineering, Mathematics, Statistics, Quantitative Finance, or a related discipline Relevant experience as a Data Scientist in building or validating AI products Solid understanding of AI models, algorithms, and the underlying mathematics Hands-on experience with Python and key data science/AI libraries (e.g., PyTorch, TensorFlow, scikit-learn) Awareness of risks associated with developing, deploying, and using AI in large commercial organizations Basic knowledge of AI-related regulations and the ability to assess the impact of proposed regulatory changes on the organization Familiarity with AI research, methodologies, and techniques, particularly General Purpose AI, Deep Neural Networks, Agentic AI frameworks, and statistical analysis (e.g., variable reduction, feature engineering) with supervised and unsupervised machine learning algorithms Expertise in data cleaning, feature engineering, and data normalization Strong interest in the latest AI tools and practices, with the ability to apply them flexibly across different organizational contexts
Offer: Annual performance-based bonus Additional bonuses for recognition awards MultiSport card Private medical care Life insurance One-time reimbursement of home office set-up (up to 800 PLN) Corporate parties & events CSR initiatives Nursery discounts Financial support for trainings and education Social fund Flexible working hours Free parking
The offer applies to permanent work.
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