Analyst, Model Risk Management

What you need to have to succeed in this role Master’s or PhD degree in a quantitative discipline like Science, Engineering, Mathematics, Statistics, Quantitative Finance, or Engineering.  Data Scientist relevant experience in building or validating AI products.  An 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. Some knowledge of the regulatory landscape or AI and ability to access the impact of proposed changes in these regulatory rules to the bank.  Some 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 Some careers shine brighter than others. If you’re looking for a career that will help you stand out, join HSBC, and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further. ABOUT THE PROJECT Model 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 locations. This enables MRM to operate consistently and efficiently globally, and to take account of additional local regulatory requirements. There is also a small Professional Practises team who provide feedback and quality assurance on validation deliverables, ensuring consistency and facilitating the sharing of internal and external best practises. 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 adoptionof AI tools and techniques throughout MRM's internal processes. WHAT WE OFFER Competitive salaryAnnual performance-based bonusAdditional bonuses for recognition awardsMultisport cardPrivate medical careLife insuranceOne-time reimbursement of home office set-up (upto 800 PLN). Corporate parties & eventsCSR initiativesNursery discountsFinancial support with trainings and educationSocial fundFlexible working hoursFree parking ,[Monitor academic, industry and internal HSBCdevelopments 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., Support the identification of opportunities to use AI tools and techniques to improve internal MRM processes., Support the adaptation or refining of 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., Support validate remediation activities completed by the ILOD to ensure appropriate resolution of identified issues., 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, PyTorch, TensorFlow, scikit-learn, Machine learning 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.