Role purpose

Financial Crime (FC) focuses on the specific financial crime threats the firm faces now and in the future, pioneering the techniques and technology that protect our business, our customers, and the many communities in which we operate from the harms associated with financial crime. FC harnesses intelligence, analytics, technology, investigation, information sharing, and public-private partnership to achieve this end, always seeking the most effective and efficient means. FC is also partnering with other areas in Compliance to build the case for a more efficient and effective regulatory approach by defining a potential new regulatory landscape based on practical, tested innovation and serving as a thought leader in the ongoing public debate on the future of regulatory compliance.

The Risk Analytics and Modelling role will develop industry-leading analytical work focused on provide cutting-edge analytic support to intelligence and investigations while pioneering techniques for discovering and targeting actual financial crime risk. The nature of the role requires intermediate - advance mathematical and programming background oriented to data analysis.

Main activities

• Driving systemic management of risk across the bank
• Promoting the conceiving, development, testing, and validation of incremental and disruptive analytic techniques to protect the bank and predict financial crime threats.
• Promoting efficient and effective outcomes across investigations and analysis, allowing fast iteration and deployment of a variety of experimental techniques into operational systems
• Delivering a data-driven approach to strategic risk modelling for financial crime risk
• Engaging to active mitigation of financial crime risks
• Ensuring experimental techniques are rigorous and purpose-built to allow for ease of approval, regulatory scrutiny, and independent validation.
• Drawing strategic context and conclusions, and presenting those findings orally and in writing to senior stakeholders to drive strategic and tactical decisions

• Intermediate - advance mathematical background
• Desirable knowledge on basic data science,
• Python programming focused on data analysis, highly required.
• Strong data visualization and communication skills.
• Familiar with technological tools used in big data (Hadoop, Spark, BigQuery).
• Knowledge in analytics methodologies for AI/ML, supervised learning, unsupervised learning, LLMs, etc.
• Basic understanding of the harms associated with the threat of financial crime.
• Ease to adopt change and develop in an environment focused on innovation and generation of new ideas.
• Excellent communication and inter-personal skills.
• Problem solving ability.

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.