Assistant Vice President - Data Science

We are currently seeking an experienced professional to join our team in the role of Assistant Vice President - Data Science.

Purpose of the role:

HSBC Asset Management is strengthening its Business Analytics capabilities to support investment decision-making, portfolio analysis, risk management and operational efficiency.

The Business Analytics team brings together investment expertise, quantitative analysis, software engineering and data science. It develops and integrates solutions that help investment professionals assess portfolios, monitor investment constraints, analyse risk and understand the drivers behind analytical results.

In this role, you will be:

• Lead the development, delivery, design, integration and industrialisation of Business Analytics and investment technology solutions that support investment decision-making, portfolio analysis, risk management and operational efficiency.
• Connect investment business needs with technology delivery by acting as a senior technology and analytics partner to investment, risk, data, operations and technology stakeholders, translating complex investment and risk requirements into practical, scalable and controlled solutions.
• Apply expertise in financial instrument pricing, financial modelling, market risk analytics, quantitative models, software engineering and solution architecture to enhance calculation capabilities for monitoring investment limits, including money market funds and other relevant portfolios.
• Design and integrate explainability capabilities into the investment analytics platform so users can understand the drivers behind analytical and risk results, ensuring models, calculations and outputs are traceable, explainable, appropriately documented and suitable for business use.
• Provide technical leadership across solution design, software engineering, data integration and application architecture, contributing to scalable and resilient architectures while integrating data science, machine learning and artificial intelligence where they deliver clear and controlled business value.
• Industrialise and extend Business Analytics applications across additional offices and locations, supporting investment restrictions and related activities while aligning with HSBC technology, architecture, security, resilience, data-quality, data-governance and information-security standards.
• Establish effective operating models between application support, data support and technology delivery teams, and work through the full delivery lifecycle, including development, integration testing, user acceptance testing, release management, production implementation, incident management, root-cause analysis and continuous improvement.
• Promote high standards of code quality, automated testing, documentation, maintainability and operational resilience; manage priorities across multiple workstreams; address dependencies, risks, resources, internal controls, risk-management requirements, audit actions and governance processes; and build trusted relationships while communicating complex technical, quantitative and data-science concepts clearly, influencing decisions through evidence and sound professional judgement.

To be successful you will be:

• A minimum of 8 years' relevant experience is mandatory in asset management, investment banking, financial technology, market risk, quantitative finance or a closely related field, together with strong investment knowledge and practical technology expertise.
• A degree or postgraduate qualification is mandatory in computer science, engineering, mathematics, finance, quantitative finance or a related discipline.
• Strong understanding of financial instrument pricing, financial modelling, quantitative investment models, pricing libraries, financial calculation engines, market-risk measures and risk-analysis techniques.
• Experience with market-risk analytics, investment constraints, portfolio analytics, investment-limit monitoring, investment restrictions, portfolio compliance or money market fund analytics.
• Strong software engineering experience in C#, C++ or Python, together with solution design and application architecture, including the integration of services, calculation engines, data sources and analytical components.
• Experience delivering technology solutions across the full lifecycle, from requirements and design through development, testing, implementation and support, with knowledge of data structures, data flows, data quality, practical data governance, cloud platforms, APIs, microservices, event-driven architectures, distributed systems, modern data platforms, data pipelines and analytical visualisation tools.
• Experience integrating data science, machine learning or artificial intelligence models into production platforms, with knowledge of model explainability, interpretability, model monitoring, model governance, DevOps, continuous integration and continuous delivery, automated testing, performance testing, production monitoring, regulatory requirements and the control environment applicable to asset management. Experience implementing solutions across multiple offices or regions is also required.
• Strong analytical and problem-solving skills, including the ability to resolve complex and unexpected issues; experience working with senior stakeholders across business, technology, risk and operations; and the ability to provide technical leadership across geographically distributed teams and time zones through expertise, influence and collaboration.

Skills

Artificial Intelligence, Asset Management, C#, C++, Data Science, FinTech, Investment Banking, Machine Learning, Market Risk, Python, Quantitative Finance