Are you a skilled data and analytics professional with a passion for transforming finance processes through modern data, automation, and AI-enabled solutions? The Finance Data & Insights Team is an agile product team responsible for the development, production, and transformation of Financial data and reporting across Consumer and Community Banking (CCB). Our vision is to improve the lives of our people and increase value to the firm by leveraging the power of our data and the best tools to analyze data, generate insights, save time, improve processes & control, and lead the organization in developing skills of the future.
As an Analytics Solutions Manager (Vice President) within the CCB Finance Data & Insights organization supporting Controllers, Treasury, and Cross Line of Business suite of products, you will partner closely with Controllers, Treasury Analytics, and Technology to deliver accurate, timely, and well-controlled financial data outcomes and solutions.
This role will play a key part in defining and product managing AI-enabled opportunities across Controller and Treasury functions. The individual will work with stakeholders to identify and map finance key job functions and families, document business requirements, assess manual activities and decision points, and help translate those opportunities into potential agentic AI use cases, product roadmaps, and implementation priorities. The role requires a blend of finance process knowledge, data and analytics experience, stakeholder management, and practical understanding of how AI, LLMs, and agentic frameworks can be applied responsibly within well-controlled financial processes.
Job Responsibilities
- Contribute to the transformation and modernization of the Finance data environment to better serve analytical and reporting needs.
- Lead discovery efforts to map finance key functions, including current-state activities, user pain points, decision points, manual handoffs, data inputs, control requirements, and potential areas for automation or AI augmentation.
- Support the development of potential agentic AI frameworks for finance use cases, including mapping tasks, workflows, prompts, data dependencies, human-in-the-loop review points, exception handling, and control considerations.
- Work with business and technology partners to evaluate where AI, LLMs, intelligent automation, and modern analytics tools can improve productivity, enhance insight generation, strengthen controls, and reduce manual effort.
- Coach and mentor the broader team on best practices, including solution generation, modern data and AI tools, and best practices for use and adoption.
- Proactively identify hidden problems and patterns in data and use those insights to drive process improvements and strengthen controls.
- Partner with Technology to design and deliver data pipelines from source systems through to end-user consumption, supporting modernization and improved scalability/reliability.
- Support agile delivery practices, including backlog management, initiative framing, sprint planning input, stakeholder demos, and communication of progress, risks, and business value.
Required Qualifications, Capabilities, and Skills
- Minimum 5+ years of experience in data analytics, financial reporting systems, product management, finance transformation, or related roles.
- Experience working with Finance, Controllers, Treasury, or financial reporting stakeholders to understand business processes, document requirements, and deliver data or analytics solutions.
- Demonstrated ability to translate complex business processes into clear requirements, use cases, user stories, process maps, and solution roadmaps.
- Practical understanding of AI, LLMs, automation, or advanced analytics concepts, with the ability to identify where these capabilities can improve business processes and user productivity.
- Demonstrated ability to drive change within organizations and manage stakeholders across multiple functions.
- Strong stakeholder management skills, including the ability to partner across Finance, Technology, Product, and senior business stakeholders to drive alignment and execution.
- Experience with financial data platforms, reporting tools, or modern data environments such as Databricks, Snowflake, data warehouses, or similar platforms.
Preferred Qualifications, Capabilities, and Skills
- Experience with AI-enabled product development, LLM-based use cases, prompt design, workflow automation, or agentic AI concepts. Experience defining or supporting AI use cases such as variance commentary generation, data quality investigation, close orchestration, reconciliation support, reporting automation, document summarization, or stakeholder self-service analytics.
- Experience with tools such as LLM Suite, Genie, Spotter, Copilot, or other enterprise AI and analytics tools. Experience with SQL, Python, Databricks, Snowflake, or other big-data query and development tools. Experience with modern BI, analytics, and automation tools such as Tableau, Alteryx, ThoughtSpot, or similar platforms.
- Familiarity with agile product management practices, including backlog refinement, user story creation, prioritization, MVP definition, sprint planning, and stakeholder demos. Ability to frame business cases for technology and AI initiatives, including qualitative and quantitative benefits such as productivity, control improvement, cycle-time reduction, scalability, and reduced manual effort.
- Understanding of data governance, data quality, lineage, access management, and control expectations in a financial services environment.