Senior Data Scientist - Wealth Management

• Define data science priorities aligned to Wealth Management strategy, feature team roadmaps and client outcomes.
• Identify opportunities to use AI, machine learning, analytics and experimentation to improve client engagement and journey performance.
• Explore emerging AI, analytics and personalisation opportunities that could transform Wealth Management client experiences.
• Analyse client behaviour, journey performance, conversion, retention and engagement trends to identify actionable opportunities.
• Partner with Product Owners and wider feature teams to define success metrics, measurement frameworks and optimisation opportunities.
• Translate complex analytics into clear business insight, recommendations and practical actions for senior stakeholders.
• Ensure data science activity is delivered responsibly within risk, control, privacy and regulatory expectations., To use innovative data analytics and machine learning techniques to extract valuable insights from the bank’s data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation., * Identification, collection, extraction of data from various sources, including internal and external sources.
• Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
• Development and maintenance of efficient data pipelines for automated data acquisition and processing.
• Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.

Vice President Expectations

• To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures..
• If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements..
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others..
• OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
• Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
• Manage and mitigate risks through assessment, in support of the control and governance agenda.
• Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
• Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
• Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
• Adopt and include the outcomes of extensive research in problem solving processes.
• Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.

• Significant experience in data science, customer analytics, AI, machine learning, or advanced analytics, applying insights to digital products, customer journeys, personalisation, growth initiatives, and client engagement.

• Strong analytical capability, with experience evaluating behavioural data, journey performance, conversion, retention, and engagement trends to drive improvement opportunities.
• Ability to translate complex technical analysis into clear business insights, recommendations, and measurable commercial or client outcomes.
• Expertise in defining success metrics, measurement frameworks, and optimisation strategies in partnership with Product teams and business stakeholders.
• Strong stakeholder management and influencing skills, combined with a proactive, opportunity-led mindset and a sound understanding of responsible data use, privacy, risk, controls, and regulatory requirements.

Desirable Skills & Experience

• Experience within financial services, wealth management, banking, fintech, or other regulated environments.
• Experience working in empowered, cross-functional teams alongside Product, Design, Research, Technology, Risk, Marketing, and Distribution stakeholders.
• Exposure to AI-driven personalisation, experimentation, predictive modelling, and optimisation of digital client experiences.
• Understanding of wealth, investing, advice, and guidance journeys, including simplifying complex financial decisions for clients.
• Experience shaping data science priorities, roadmaps, or AI strategies within product-led organisations, with strong commercial awareness and the ability to link digital experience improvements to business growth and client outcomes.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.