Barclays
Banking
BankingProductAnalyticsVP
Neural analysis suggests this role is
optimal for Lead candidates.
“Banking Product Analytics VP at Barclays. Skills: data analytics, machine learning, statistical models, predictive models, Data Science, GenAI, advanced AI technologies. Identification, collection, extraction of data from various sources. Performing data cleaning, wrangling, and transformation”
What You'll Achieve.
inform strategic decision-making; improve operational efficiency; drive innovation across the organisation; ensure unapparelled customer experiences; deliver insights across loans, deposit, and emerging products; lead analytics modernization; achieving the goals of the business
Industry & Context.
extract valuable insights; analyse patterns, trends, and relationships; forecast future outcomes; identify potential risks and opportunities; seek out opportunities to add value from data; create solutions based on sophisticated analytical thought; define problems; develop innovative solutions; adopt and include the outcomes of extensive research in problem solving processes; translate business problems into scalable analytical solutions
What They're Looking For.
Must Have
data science, advanced analytics, quantitative analytics, deposit and lending analytics, product performance, customer behaviour, pricing and offer optimization, campaign analytics, portfolio management, Python, SQL, SAS or equivalent, operationalizing analytics in production settings, risk and controls, change and transformation, business acumen, strategic thinking, digital and technology, job-specific technical skills
Nice to Have
GenAI, advanced AI technologies, LLM-enabled analytics, retrieval-augmented generation (RAG), agent-based or workflow-driven analytics, enterprise knowledge systems, financial services organizations, banking and consumer finance businesses, technology-driven, platform-led IT consulting or advisory experience across multiple organizations, enterprise analytics and AI operating models, centralized and federated delivery structures, reusable platforms, driving change and adoption of analytics, cloud, and AI solutions, training, enablement, and stakeholder engagement, data governance, data quality, analytics industrialization, evaluating build‑vs‑buy decisions, managing vendor partnerships, assessing cost, scalability, and risk trade‑offs for analytics and AI platforms, responsible AI principles, model risk considerations, regulatory expectations for advanced analytics and AI in financial services
What You'll Do.
extraction of data from various sources
Performing data cleaning
Development and maintenance of efficient data pipelines
Design and conduct of statistical and machine learning models
Development and implementation of predictive models
Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science
lead analytics modernization through cloud adoption
and advanced AI‑enabled analytics
How You'll Work.
Team & Collaboration
Collaborate with business stakeholders; Partner effectively with Product, Technology, Risk, Controls, and Business stakeholders; Collaborate with other areas of work, for business aligned support areas; lead collaborative, multi-year assignments; guide team members through structured assignments; identify the need for the inclusion of other areas of specialisation; train, guide and coach less experienced specialists
Communication Scope
Advise key stakeholders; communicate complex analytical and AI concepts to senior executives; translating technical outputs into clear business and risk insights
Process & Methodology
Plan resources, budgets, manage and maintain policies, deliver continuous improvements, escalate breaches of policies/procedures, planning for the department’s future needs and operations, balancing short and long term goals, ensuring that budgets and schedules meet corporate requirements, lead collaborative, multi-year assignments
Full 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. **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 stan
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