As one of the world’s largest banking and financial services organisations, HSBC has been connecting customers to opportunities since 1865. With operations in 63 countries and territories, HSBC’s unparalleled international network links developed and emerging markets, and spans the world’s largest and fastest-growing trade corridors. The bank serves more than 40 million customers through its commercial, retail, investment and private banking businesses, which are supported by operational and functional teams around the world.
Our Data and Data Solutions team sits within HSBC Securities Services (SSv), driving the strategic use of data and AI to enhance operational efficiency, risk management and client solutions. We oversee:
Master Data Management & Governance – Ensuring data is accurate, consistent, well catalogued and compliant for both traditional analytics and AI use cases.
Data Platforms & Catalogues – Managing scalable platforms (e.g. Data Mesh, HSBC Evolve) and metadata/catalogues that enable seamless data and AI asset discovery.
Access Management, Risk & Controls – Safeguarding data and AI workflows through robust security, entitlements, lineage and model governance.
Reporting, Analytics & Managed Services – Delivering actionable insights and KPIs via standard reports, interactive dashboards and data services to internal teams and clients.
Automation, AI & Data Innovation – Embedding machine learning, LLMs and agentic workflows into core processes (e.g. onboarding, reporting, reconciliation, knowledge management) to unlock new value at scale.
By partnering with Product, Operations, Technology, Risk, Client Services and Group AI, we empower the business with trusted, AI ready data and intelligent solutions that meet regulatory demands and drive competitive advantage across Securities Services.
As the Senior Product Analyst, you will act as a business intelligence and AI product architect, partnering with Product, Operations, Technology and Client Services to:
Design & Standardise AI Ready Securities Services KPIs
Define and maintain core metrics (e.g. settlement fails, STP rates, NAV timeliness, client SLA adherence) aligned to business, risk and client objectives.
Embed data quality, lineage and control checks to ensure KPI and model input accuracy across systems and jurisdictions.
Build Next Generation Data & AI Visualisation Solutions
Design and deliver interactive dashboards and AI enabled analytics on HSBC Evolve for:
Operational Health – Real time monitoring of post trade workflows, exceptions and AI driven alerts.
Client Reporting – Customisable, self service views of asset servicing performance, enriched with predictive and AI assisted insights.
Help automate regulatory and management reporting using strategic data platforms, APIs and AI services, reducing reliance on legacy EUCs and manual processes.
Drive Data & AI Literacy and Adoption
Train business users on self service analytics tools, AI assisted features and KPI interpretation, promoting safe and effective use of AI outputs.
Lead workshops and design sessions to identify reporting and AI opportunity gaps, and to continuously improve dashboard UX, data services and AI enabled workflows.
Why This Role Matters
Your work will directly:
Reduce manual reporting and data preparation efforts by shifting users onto automated, AI enabled data and reporting platforms.
Enable proactive risk and performance management through trusted KPIs, real time dashboards, intelligent alerts and AI driven diagnostics.
Equip clients and internal teams with transparent, on demand, AI enhanced performance metrics and insights, strengthening HSBC’s competitive edge and positioning SSv at the forefront of data and AI driven securities servicing.
Key Responsibilities
Assess data and AI readiness across multiple platforms by performing data gap, quality and lineage analysis to ensure KPI calculation, AI model inputs and visualisation outputs are accurate, complete and governed.
Elicit and document business requirements, user stories and functional specifications for AI and data driven products delivered through web portals such as Evolve.
Design end to end process maps and AI enhanced workflows, showing how data flows from source systems to Data Mesh / Fabric, through AI models and orchestration layers, to reporting and client facing channels, including human in the loop control points.
Work with architecture and data teams to define data models, reference data usage and semantic layers that support both traditional analytics and AI use cases (LLM, RAG, ML based matching/anomaly detection).
Act as primary liaison between business stakeholders, data/AI teams and technology within agile pods to deliver AI enabled data, reporting and workflow solutions on strategic platforms.
Help shape product backlogs and roadmaps for AI initiatives, prioritising use cases, features and technical enablers based on business value, risk, data readiness and regulatory commitments.
Define and execute test strategies for both data and AI components (e.g. field mappings, KPI calculations, model suggestions, recommendation quality), including UAT, AI output sampling, regression checks and explainability / guardrail tests to meet internal and regulatory standards.
Support migration and rollout strategies as we transition from legacy reports, EUCs and manual workflows to strategic AI enabled platforms, including pilot design, controlled ramp up and benefits tracking.
Partner with Operations, Product and COO teams to define and refine standard KPIs for Securities Services (e.g. STP%, Fail Trade%, NAV timeliness, exception volumes, turnaround times), ensuring they are embedded in dashboards, AI workflows and control frameworks.
Use data and AI generated insights (e.g. usage, reconciliation exception trends, onboarding cycle times) to identify root causes, optimisation opportunities and automation candidates, presenting clear recommendations to senior stakeholders.
Facilitate training and adoption of AI and data enabled tools for business users, focusing on data literacy, AI literacy and safe, effective use of AI outputs.
Act as a trusted partner and “translator” between technical AI teams and business stakeholders, ensuring risk, compliance, client and operations perspectives are incorporated in design and delivery.
Benchmark SSv’s data and AI capabilities against industry standards and fintech solutions, identifying gaps and differentiating opportunities.
Research and propose innovative AI and analytics capabilities, such as predictive risk and capacity forecasting, AI driven alerts, intelligent exception handling, knowledge based copilots, and agentic workflows for onboarding, reporting and operations.
Work with data and governance teams to enhance data and AI practices (e.g. standard feature stores, reuse of models, shared ontologies, improved lineage and metadata) aligning with Group AI and data governance frameworks (AIRCo, DSTORE, data visas).
Support cross functional initiatives that span multiple domains (e.g. client onboarding, treasury and liquidity analytics, pricing and billing, regulatory reporting, client 360 analytics) where AI and data are key enablers.
Maintain awareness of Securities Services and CIB trends in AI, data, digital platforms and regulation, and incorporate those insights into roadmaps, requirements and design choices.
Contribute to the ongoing evolution of HSBC’s enterprise data and AI operating model, including workflow management standards, AI risk controls, MRM compliant design patterns and reusable templates that can be used across SSv and CIB.
If you are interested in this role, click “Apply”
HSBC is committed to building a work culture where everyone is valued, respected and opinions count. They take pride in providing a workplace that fosters continuous professional development, collaboration and supporting people to be at their best in an inclusive and diverse environment.
Type: Contract
Category: I.T & T - Business Analysis
Reference ID: 117-160920261-LL
Date Posted: 16/09/2026
