Assistant Vice President, Model Risk Management (AI CoE) @ HSBC Technology Poland

HSBC

  • Kraków, małopolskie
  • Stała
  • Pełny etat
  • 10 dni temu
EXPERIENCE:
  • Master’s or PhD degree in a quantitativediscipline like Science, Engineering,Mathematics, Statistics, Quantitative Finance,or Engineering.
  • Data Scientist relevant experience in buildingor validating AI products.
  • Deep understanding of AI models, algorithms and the associated mathematics.
  • Experience with Python, including the main libraries used for data science and AI (e.g.PyTorch, TensorFlow, scikit-learn).
  • Knowledge of the risks associated with developing, deploying and using AI in large commercial organizations.
  • Knowledge of the regulatory landscape for AI and ability to access the impact of proposed changes in these regulatory rules to the bank.
  • Knowledge of AI research, methodologies and techniques, particularly General Purpose AI,
  • Deep Neural Networks, Agentic AI frameworks and statistical analysis (Variable Reduction, Feature engineering) with Supervised and Unsupervised machine learning algorithms.
  • Expertise with data cleaning, feature engineering, and data normalization techniques.
  • Active interest in the latest tools and ways of working linked to AI, with the ability to apply this knowledge in a flexible way adapting to varied circumstances across HSBC.
  • Ability to promote a strong risk control culture and continually improve risk awareness.
  • Ability to develop networks with key stakeholders.
  • Providing advice and challenge, delivering risk management policies and managing risks and controls.
ABOUT THE PROJECTModel Risk Management (MRM) at HSBC is structured as a global function, headed up by the Chief Model Risk Officer (CMRO). MRM are the second line of defence (2LoD) for Model Risk and the CMRO is the global Model Risk Steward for the group and is also accountable for the global operation of the MRM function. MRM teams are based in each region, to ensure local subject matter expertise and to guide, review, and challenge. MRM activity is managed on a global basis as many models are used in multiple
l ocations. This enables MRM to operate consistently and efficiently globally, and to take account of additional local regulatory requirements.
The MRM AI COE is a team within IMR comprising AI specialists which provides leadership, standards, coordination, and subject matter expertise for all AI activities across MRM, including validation, to ensure MRM’s treatment of AI throughout the model lifecycle is effective, efficient, consistent and current. They work with the Infrastructure Team to advance the adoption of AI tools and techniques throughout MRM's internal processes.WHAT WE OFFER
  • Competitive salary
  • 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 with trainings and education
  • Social fund
  • Flexible working hours
  • Free parking
,[Monitor academic, industry and internal HSBC developments in AI tools, techniques and ways of working to support a forward-looking agenda for emerging risks and challenges that, ERM and the Bank may face, and ensure MRM’s approach to AI remains effective, efficient and up to date., Undertake AI related model validation activities as dictated by the Global Model Risk Policy including the assessment of; model inputs, calculations, reporting outputs, conceptual soundness of the underlying theory and the suitability of the use for its intended purpose, relevance and completeness of data, qualitative information and judgements, documentation, and implementation of the model., Identify opportunities to use AI tools and techniques to improve internal MRM processes., Adapt or refine existing AI tools to enable their use for internal MRM processes., Provide written reports detailing the results of validations highlighting issues identified during the validation., Validate remediation activities completed by the ILOD to ensure appropriate resolution of identified issues., Work with relevant stakeholders to support the embedding of new Global Model Risk Policies and Procedures, Provide model users, model owners, senior management, audit, and regulators (across 1LOD, 2LOD, 3LOD) with confidence that the models and tools developed, maintained, and used within the Group are compliant with internal and regulatory expectations and fit for the intended purpose., Help build management, regulatory, and external confidence in all models used across the group] Requirements: PhD, Degree, AI, Python, Data science, TensorFlow, scikit-learn, Machine learning, risk management Additionally: Training budget, Private healthcare, Flat structure, International projects, Multisport card, Monthly remote work subsidy, Psychological support, Conferences, PPK option, Annual performance based bonus, Integration budget, International environment, Small teams, Employee referral bonus, Mentoring, Workstation reimbursement, Company share purchase plan, Childcare support programme, Bike parking, Playroom, Shower, Canteen, Free coffee, Free beverages, Free parking, In-house trainings, In-house hack days, No dress code, Modern office, Knowledge sharing, Garden, Massage chairs, Kitchen.

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