Modelling Analyst

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HSBC is one of the largest banking and financial services organizations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realize their ambitions.

We are currently seeking an experienced professional to join our team in the role of Modelling Analyst

Purpose of the role

Analytics, Digital and Architecture (ADA) is a recently established function within Global Finance. Analytics, Digital and Architecture (ADA) aim is to be the pioneering force shaping the future of analytics, engineering, and innovation to empower insight and strategic decision making in Finance. Analytics, Digital and Architecture (ADA) is a globally diverse team; this role is a senior role within the Finance Analytics section of this wider team. Within Analytics, Digital and Architecture (ADA), The Analytics team is responsible for model development and advanced analytics in Finance. This is a role looking to bring technical expertise to the team. The focus will be on developing various analytics applications within Finance. This will involve using statistical modelling, Machine Learning algorithms and quantitative expertise to develop appropriate solutions, building methodologies in Python, handling the model lifecycle, co-ordinating projects, and use of resources across geographies. We seek a candidate with expertise in model development and python programming to contribute and complete project deliveries. Additionally, it requires managing relationships with stakeholders within Finance. The Analytics, Digital and Architecture (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.

In this role, you will:

• The jobholder is responsible for developing best in class statistical/analytical/Machine Learning (ML) models and deploying these across various products & portfolios for global finance internal programs.
• Undertake operations for the development and deployment of new tools and modelling techniques – Python, Machine Learning solutions, cloud (preferred) to live business problems on a day-to-day basis.
• Develop and write clean, efficient, and well-documented code, with a strong focus on scalability and maintainability. Experience with version control (Git) and collaborative development practices.
• Lead and contribute across the various stages of modeling life cycle, like defining model scope to model development, validation, testing, documentation, scenario analysis, etc.
• Monitor the evolving regulatory needs, reporting standards and understanding their impact on the models. Work and collaborate with multiple stakeholders/functions on multiple projects simultaneously and deliver in a timely, efficient, and effective manner, while understanding the overall objective.
• Manage relationships with key stakeholders in the Business (Onshore and Offshore) to build confidence. Liaising with IMR to provide support during their review, manage the action plan arising from their review, adapt model, and document accordingly.
• Responsible for observing all the applicable compliance policies (Data security policy,  Anti Money Laundering (AML), operational risk, Functional manual, Group Compliance Manual, Audit recommendations, Internal Control requirements, regulatory guidelines etc.) and business standards of Organization as applicable.
• Responsible for taking timely action on Audit comments and demonstrate compliance with Internal controls. Conduct continuous review of process with the objective of improving the efficiency and quality of deliverables. Ideate, develop & deploy operational efficiency enhancing solutions using new tools, techniques, and technology.

To be successful you will:

• 1+ years of prior experience in Statistical/ Financial/ Mathematical Modeling, Data analytics, and large data handling. Masters or Ph. D in Mathematics, Economics, Statistics, Engineering, MBA, or equivalent
• Relevant experience in analytics specifically in fields such as Treasury Analytics, Machine Learning, anomaly detection, time-series and forecasting modeling etc. for a Banking organization
• Proficient in Python with a strong grasp of object-oriented programming, data structures, and algorithms. Experience with libraries such as NumPy, Polars, Scikit-learn, TensorFlow and PyTorch.
• Strong analytical skills with demonstrated problem solving skills. Ability to comprehend an intricate and diverse range of business problems and analyze them with limited or complex data and provide a feasible solution framework.
• Commercial acumen – good knowledge of Banking products and its dynamics, conceptual soundness of related financial ratios, P&L and drivers.
• Ability to work in cross-functional teams with strong interpersonal skills and drive for success. Excellent written and verbal communication skills. Ability to develop and effectively communicate complex concepts and ideas.
• Strong relationship management skills across a diverse organization, especially with senior management
• Must have excellent attention to detail and work within tight deadlines ensuring a complete and accurate flow of information's between stakeholders.

You’ll achieve more when you join HSBC.

www.hsbc.com/careers

HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.”

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