AVP, Technology Risk Analytics & Digital Insights Lead

The Mission

We are seeking a hands-on analytics lead with proven experience designing and developing dashboards for senior stakeholders, ideally in risk, technology, audit, or similarly complex domains.

This is not a pure reporting, data engineering, or platform build role. The emphasis is on insight, narrative, and analytical judgement, using Tableau as the primary storytelling tool, supported by robust data preparation and analysis using Excel, Access, SQL, and Python.

You will work closely with Technology Risk teams and stakeholders to translate complex datasets into clear themes, trends, and implications suitable for executive and committee-level discussion.

Responsibilities:

1. Risk Analytics & Dashboard Storytelling

• Design, build, and maintain Tableau dashboards that support narrative, insight, and executive discussion.
• Apply strong visual and analytical judgement to highlight what matters most and avoid unnecessary complexity or data overload.
• Develop dashboards related to Technology Risk, controls, incidents, or performance analytics where interpretation and context are critical.
• Continuously refine dashboards based on stakeholder feedback and evolving risk questions.

1. Analytical Development & Data Preparation

• Perform detailed analytical work using Excel and Access, including modelling, reconciliation, and exploratory analysis.
• Structure, clean, and integrate datasets from multiple sources to support consistent, repeatable analysis.
• Conduct deep-dive analysis on incidents, control performance, emerging risks, and thematic issues to support dashboard narratives.

1. Analytical Programming & Automation

• Use SQL to extract, join, and shape data for analysis and Tableau visualisation.
• Use Python (or a similar language) for data transformation, exploratory analysis, automation, and repeatable workflows.
• Build lightweight automation to reduce manual effort and improve consistency of analytical outputs.

1. Use of Generative AI for Insight Generation

• Leverage GPT-based tools to accelerate analysis, summarise large volumes of text, and identify patterns in unstructured data (e.g., incident descriptions, audit observations, committee materials).
• Use AI as an analytical assistant to enhance thinking and efficiency while ensuring clear interpretation and validation of outputs.
• Identify value-driven, practical ways AI can support Technology Risk insight generation.

1. Stakeholder Partnership

• Partner closely with Technology Risk teams, reporting leads, and First Line stakeholders to align analytics with decision needs.
• Support consistent interpretation of dashboards and metrics across stakeholders.
• Provide input on data capture and structure to improve downstream analysis and insights.

Requirements:

1. Core Skills

• Advanced proficiency in Tableau with proven experience building insight-driven dashboards for senior stakeholders.
• Strong Excel capability, including complex formulas, data modelling, and analytical workflows.
• Experience using Access or similar tools for structured data analysis.
• Strong SQL capability for querying, joining, and shaping data.
• Working proficiency in Python (or similar scripting language).
• Practical experience using Generative AI tools (e.g., GPTs, copilots) to support analysis and pattern identification.
• Strong written communication skills with the ability to produce concise analytical summaries.

2. Experience & Background

• 5+ years' experience in analytics, business intelligence, technology risk, risk management, or related fields.
• Demonstrable experience developing dashboards where interpretation and context matter-not just data presentation.
• Experience working with risk, control, technology, or operational data (strongly preferred).
• Degree in a quantitative, analytical, or related discipline, or equivalent practical experience.

3. Nice to Have

• Tableau certification.
• Experience in banking, financial services, or other regulated environments.
• Risk or audit qualifications (e.g., CISA, CRISC), secondary to analytical capability.

4. Success Profile

• Experienced in owning dashboards end-to-end-from raw data to executive-ready visuals and commentary.
• Applies sound judgement on when analysis is sufficient, prioritising clarity and decision impact over complexity.
• Comfortable with loosely defined problem statements and able to convert broad questions into structured analysis.
• Strong instinct for storytelling with data, particularly in risk, technology, or similarly nuanced domains.
• Able to explain technical findings clearly to non-technical senior stakeholders.