• Dashboard and MI build expertise - Tableau, Qlik Sense, Power BI
• Data & analytics capability - Python; ideally also SQL
• Wholesale credit / wholesale banking / W-IRB knowledge

Our client – Leading banking firm management company, is now looking for Model Advisory & Management Director within their team.

Role overview

The role delivers an effective model advisory & management capability in Corporate and Institutional Banking (CIB) and sits in the Model Advisory & Management team under Credit and Capital Management. You’ll lead the development of a data and analytics capability that provides timely, decision-ready insights on Wholesale IRB (W‑IRB) model for senior business stakeholders. Working with regional and global stakeholders across Business, Risk and Finance across the model lifecycle, you’ll help strengthen risk management, support effective regulatory compliance, and deliver measurable business outcomes.

This is a hybrid role based in Hong Kong.

Key Responsibilities

• Model Impacts: Develop an analytical capability to provide comprehensive and timely insights to business audience on W-IRB model impacts to inform business decisions
• Model Insights: Develop a one-stop-shop visualisation dashboard for key Model MIs with the potential to further include information such as credit quality, capital and return.
• Data Assets: Identify and create a reference catalogue for key data assets we use, including data dictionaries, high value use cases, programming / coding for various key insights.
• Model Optimisation: Use data & analytics to identify areas of gaps and opportunities across model inputs, model design, use of model outputs, credit risk policies, systems and processes to enable commercial and capital efficiency.
• AI Adoption: Ideate use cases and develop tools, capabilities and prompt libraries to embed AI into the team’s activities to improve efficiency, speed and performance.
• Regulatory Landscape: Keep abreast of regulatory changes; assess impacts to CIB business, global/regional strategy, and business outcomes.
• Knowledge Assets: Create a repository and deliver teach-in sessions to expand the team’s expertise on topics such as climate risk data & modelling and economic capital modelling.
• Model Advisory: Act as a technical and commercial subject matter expert, providing clear insights, guidance, and support on W-IRB model matters to a wide range of senior stakeholders across Business and Risk.

Skills and Experience

Essential (must-have)

• Advanced data & analytics capability with proven experience solving complex business problems using large datasets and coding (e.g., Python; ideally also SQL), including data wrangling, analysis, and automation of repeatable insights.
• Dashboard and MI build expertise: strong hands-on experience designing and building executive-ready visualisation dashboards (e.g., Tableau, Qlik Sense, Power BI, Dash/Plotly), including KPI definition, drill-down design, performance considerations, and user adoption.
• Insight generation and executive storytelling: demonstrated ability to translate analysis into clear, commercially relevant insights and recommendations, and present them confidently to business and executive-level stakeholders (clear narrative, crisp visuals, decision-focused messaging).
• Data governance and asset management: experience creating and maintaining data assets such as data dictionaries, reference catalogues, lineage/definitions, and reusable code artefacts to enable consistent MI and self-serve analytics.
• Demonstrable, hands-on experience applying GenAI to improve productivity and quality of outputs.
• Responsible AI and control mindset: strong awareness of data confidentiality, model risk, and operational controls when using AI/GenAI; able to design guardrails (e.g., approved use cases, prompt hygiene, human-in-the-loop checks, documentation).
• Model optimisation mindset: experience identifying gaps/opportunities across model inputs, model outputs, policies, systems and processes, and driving improvements that enhance commercial and capital efficiency.
• Wholesale credit / wholesale banking / W-IRB knowledge: strong working knowledge of wholesale banking and credit risk, including how W‑IRB model inputs/outputs are used across the credit lifecycle (risk rating, origination/monitoring, RWA/capital, pricing/returns) and how model impacts translate into business / commercial outcomes.
• Stakeholder management in a matrixed environment: proven ability to partner effectively across Business, Risk and Finance, align requirements, manage expectations, and deliver outcomes at pace.
• Strong delivery discipline: excellent prioritisation and execution skills in an agile, dynamic environment; track record of taking work from ambiguity to measurable outputs.

Preferred (nice-to-have)

• Experience operationalising AI/analytics solutions (e.g., version control such as Git, documentation standards, testing/controls, reproducible pipelines; working with technology partners to productionise dashboards/MI).
• Familiarity with the regulatory landscape impacting IRB/model risk and wholesale credit, with ability to translate regulatory change into MI, analysis and business implications.
• Exposure to economic capital and/or climate risk data & modelling, and experience building knowledge assets/teach-ins for broader teams.
• Experience with modern data platforms (cloud/on-prem data lakes/warehouses) and performance optimisation for large-scale reporting/MI.

Interested parties please email a MS Word version resume and expected salary to  aston.yeung@manpowergrc.hk (cc: it@manpower.com.hk) and quote the job reference no.