Securities Services - Analytics, AI & Data Strategy - Product Manager - Vice President

Securities Services, a division of J.P. Morgan’s Corporate Investment Bank, is a global industry leader with over $30 trillion in assets under custody. J.P. Morgan provides innovative custody, fund accounting and administration services to the world's largest institutional investors, alternative asset managers and debt and equity issuers. J.P. Morgan's Securities Services business is comprised of Custody, Accounting, Transfer Agency, Middle Office outsourcing, Foreign Exchange, and other activities related to servicing assets for traditional and alternative funds; it leverages its scale and capabilities in more than 100 markets to help clients optimize efficiency, mitigate risk and enhance revenue through a broad range of investor services as well as securities clearance, collateral management and alternative investment services investments around the world.

Job Summary

The Analytics, AI & Data Strategy team provides data-driven business intelligence to all major stakeholder groups within Securities Services. You will work with stakeholders across the Securities Services franchise to build strategic analytics, AI and data capabilities which will enable the organisation to optimise revenue and develop a strong risk mitigation framework.

Within the Securities Services Analytics, AI & Data Strategy team, you will be part of a team responsible for the delivery of business-critical data and analytics deliveries relating to themes such as liquidity exposure, deposit management, risk management & revenue maximization.

Job Responsibilities

• Defining the future 3-5 year Securities Services strategy relating to large-scale analytics, AI and data programs & architectures, including executing Securities Services’ data, analytics and AI deliveries across all major products and stakeholder groups
• Developing AI and analytical models to identify patterns in data, spot data anomalies & predict client behaviour, all of which facilitate error reduction & revenue optimisation
• Conducting Quarterly Business Reviews (QBRs) to showcase the value-add of analytics, AI and data for the Securities Services franchise, including the delivery of a cohesive communication strategy on data modernization to all major stakeholder groups (including Product, Sales, Technology and cross-CIB data organisations)
• Acting as the main global escalation point for product-related questions and ensure suitable resolution and management of risks such as data bottlenecks
• Responsibility for the implementation and tracking of Securities Services’ data modernization and AI initiatives, including chairing monthly senior management Steering Committees
• Serving as the primary program and project leader to manage stakeholder meetings, ensure that the work is moving forward in a timely manner and according to the agreed execution roadmaps
• Working with the global product and wider stakeholder teams to create a consistent analytics, AI and data execution model from a requirement prioritisation and governance standpoint (where applicable)
• Support Ad-hoc research and resolution of daily issues, data requests, reporting requirements, as well as any regulatory requests that impact data and analytics deliveries
• Articulating complex ideas and analytical deliveries in a succinct way, including being comfortable recording demos and presenting to large audiences

In addition to this, you will be responsible for supporting the investment funding strategy for the Securities Services’ Analytics, AI & Data Strategy team, helping to ensure that critical programs with a high return-on-investment (ROI) are efficiently and seamlessly funded. Core responsibilities include:

• Developing a robust understanding of the Securities Services product offerings and working with the respective business representatives and other stakeholder groups to document business requirements that need investment funding
• Coordinating the Investment Planning (IP) process to ensure continued funding for analytics, AI and data strategy requirements, including pitching for new investments at senior management forums
• Coordinating with Product Management, Product Development, Sales, Quantitative Research, Finance, Business Management and Technology to deliver all funded milestones, including tracking all delivery milestones for data publication, ingestion & consumption
• Managing and communicating resource demand vs. current capacity, including the prioritisation of new business asks against the existing book of work

Required qualification, capabilities and skills

• A successful candidate will have worked in financial services (e.g. in Securities Services, Payments, Treasury, Fintech, or any Corporate/Investment Banking function) with a data/analytics background for a minimum of 5 years
• The candidate should have a background in a Product Management, Project Governance, Product Development or Technology role and have an Undergraduate degree
• Experience with working with technology and/or data scientists to build analytics/AI products is a must-have
• Excellent written and oral communication and presentation skills, with experience communicating effectively with diverse audiences – across business and technology partners, including senior leadership
• Strong influencing skills, with an ability to articulate complex ideas and analytical deliveries in a succinct way
• Ability to influence and effectively lead cross-functional teams in a fast-paced environment where there are multiple, urgent priorities with short deadlines
• Experience leading a team and developing talent, managing projects and using project management tools (e.g. JIRA, confluence, Microsoft Teams)
• Self-starter with out-of-the box problem-solving skills, able to bring new ideas to life, particularly where business requirements are unclear/incomplete
• Excellent time management skills, with the ability to multi-task and keep numerous projects on track
• Keen attention to detail, strong organization skills and thorough follow-up when bottlenecks prevent certain programs from being delivered

Preferred qualification, capabilities and skills

• Comprehensive IT knowledge - full suite of Microsoft Office products and ideally Alteryx and/or Tableau knowledge to support data mining and data modelling
• The undergraduate degree should have some components relating to a quantitative field (e.g. Computer Science, Data Analytics, Economics, Statistics modules etc.)
• Basic knowledge of AI modelling techniques that can be leveraged within the banking sector (e.g. supervised and unsupervised Machine Learning models)