AVP, Modeling and Analytics

 In compliance with applicable laws, HSBC is committed to employing only those who are authorized to work in the US. Applicants must be legally authorized to work in the U.S. as HSBC will not engage in immigration sponsorship for this position.  Our purpose – Opening up a world of opportunity – explains why we exist. Here at HSBC we use our unique expertise, capabilities, breadth and perspectives to open up new kinds of opportunity for our more than 40 million customers. We’re bringing together the people, ideas and capital that nurture progress and growth, helping to create a better world – for our customers, our people, our investors, our communities and the planet we all share.Analytics, Digital and Architecture (ADA) is a recently established function within Global Finance. ADA’s aim is to be the pioneering force shaping the future of analytics, engineering, and innovation to empower insight and strategic decision making in Finance. ADA is a globally diverse team. The ADA Analytics team aims to ensure that Finance develops models, methodologies and other analytics that bring tangible benefit to the users, housed within a robust framework and compliant with regulatory rules.As our AVP, Modeling and Analytics you will:Manage the model life-cycle, while engaging with business and finance teamsEnsure that the models continue to be fit for purpose via establishing an effective model validation frameworkMaintain documentation and control for models in line with internal policies and regulatory guidanceOnboard and maintain models on internal model execution platformsWorking with business partners to provide financial and technical analysis and recommendations regarding current and/or proposed PPNR modelsWorking with businesses, risk and finance teams to submit and validate data and analyze the consolidated resultsDevelopment/enhancement of models, methodologies and infrastructure across Finance predominantly related to forecasting, stress testingYou´ll likely have the following qualifications to succeed in this role:Minimum qualifications:Advanced (masters or PHD equivalent) degree in a quantitative (e.g. science, mathematics, engineering, econometric, financial engineering) field.Experience in developing timeseries, regression modelsProficiency in Python with experience using libraries like NumPy, Polars, Scikit-learn, TensorFlow and PyTorchStrong ability for problem solving and attention to detailStrong communication, analytical, and presentation skillsGood to have:5+ years of relevant work experienceKnowledge of bank stress testing and CCAR requirementsExperience building machine learning modelsCommercial acumen – good knowledge of Banking products and its dynamics, conceptual soundness of related financial ratios, P&L and driversAbility to operate in a fast-paced environment and with all levels of internal and external management and government regulators As an HSBC employee, you will have access to tailored professional development opportunities to ensure you have the right skills for today and tomorrow. We offer a competitive pay and benefits package including a robust Wellness Hub, all in a welcoming and inclusive work environment. You will be empowered to drive HSBC’s engagement with the communities we serve through an industry-leading volunteerism policy, a generous matching gift program, and a comprehensive program of immersive Sustainability and Climate Change Initiatives. You’ll want to join our Employee Resource Groups as they play a central part in life at HSBC, including the development of our employees and networking inside and outside of HSBC. We value difference. We succeed together. We take responsibility. We get it done. And we want you to help us build the bank of the future The final fixed pay offer will depend on the candidate and a number of variables, including but not limited to, role responsibilities, skill set, depth of experience and education, licensing/certification requirements, internal relativity, and specific work location.    All qualified applicants will receive consideration for employment without regard to age, ancestry, color, race, national origin, ethnicity, disability or medical condition, genetic information, military or veteran service, religion, creed, sex, gender, pregnancy, childbirth, caregiver status, marital status, citizenship or immigration status, sexual orientation, gender identity or expression or any other trait protected by applicable law.