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Job details
Job ID
JR-0000131073
Job description
Job Description
Purpose of the role 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.
Accountabilities
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.
Assistant Vice President Expectations
To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
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 lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
Take ownership for managing risk and strengthening controls in relation to the work done.
Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
Influence or convince stakeholders to achieve outcomes.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
Embark on a transformative journey as a Banking Product Analytics AVP at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. Credit, Fraud & Decision Management (CFDM) is a core analytics and decisioning organization supporting Barclays’ US Consumer Banking businesses. Within CFDM, the Banking Products Analytics team delivers insights across loans, deposits, and emerging products, while leading analytics modernization through cloud adoption, automation, and advanced AI‑enabled analytics.
To be successful in this role as a Banking Product Analytics AVP, you should possess the following skillsets: · Experience in data science, advanced analytics, or quantitative analytics, with demonstrated application in complex, regulated business environments. · Hands‑on experience across both deposit and lending analytics, including product performance, customer behaviour, pricing and offer optimization, campaign analytics, and portfolio management. · Strong expertise in machine learning and advanced analytical techniques · Proven experience with GenAI and advanced AI technologies, including LLM‑enabled analytics, retrieval‑augmented generation (RAG), agent‑based or workflow‑driven analytics, and enterprise knowledge systems. · Demonstrated ability to lead and develop analytics teams, including direct or matrix management of two or more analysts, setting analytical standards, and reviewing complex analytical deliverables. · Experience in leading financial services organizations, with exposure across a range of banking and consumer finance businesses, complemented by experience operating in or partnering with technology‑driven, platform‑led IT companies; consulting or advisory experience across multiple organizations preferred · Strong proficiency in analytics programming and data platforms commonly used in banking environments (e.g., Python, SQL, SAS or equivalent), and experience operationalizing analytics in production settings. · Ability to partner effectively with Product, Technology, Risk, Controls, and Business stakeholders to translate business problems into scalable analytical solutions. Some other highly valued skills include: · Experience designing and operating enterprise analytics and AI operating models, including centralized and federated delivery structures and reusable platforms. · Strong capability in driving change and adoption of analytics, cloud, and AI solutions across business teams, including training, enablement, and stakeholder engagement. · Deep understanding of data governance, data quality, and analytics industrialization, ensuring solutions are scalable, auditable, and production‑ready. · Experience evaluating build‑vs‑buy decisions, managing vendor partnerships, and assessing cost, scalability, and risk trade‑offs for analytics and AI platforms. · Proven ability to communicate complex analytical and AI concepts to senior executives, translating technical outputs into clear business and risk insights. · Strong awareness of responsible AI principles, model risk considerations, and regulatory expectations for advanced analytics and AI in financial services. 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.
