JPMorgan Branded Card - Financial Analysis Associate 

United States, Delaware, Wilmington 

329510118

We are seeking an associate for financial management, planning and analysis for the Sapphire portfolio as well as cross-product support.

As a Financial Analysis Associate in the Chase Branded Cards CFO team, you will be responsible for

Job Responsibilities:

• weekly / monthly / quarterlyreporting, projects and ad hoc analysis that provide insights into portfolio, product, and customer behavior
• Analyze financial results and forecasts to provide recommendations on performance to finance and business clients and stakeholders
• Create and maintain multi-year financial models, assessing the impact of strategic decisions and trade-offs on the P&L
• Develop financial business cases to support variousinitiatives
• Be responsible for socialization and submission of budget and technology book of work
• Preparing senior management presentations to help drive strategy
• Partner closely with Analytics and Finance teams, including P&A, CCAR Forecasting, and Investment Valuation teams

Required Qualifications, Capabilities, and Skills:

• Bachelor’s degree in Finance, Accounting or related subject
• 3+ years of work experience in Financial Services and/or accounting/controller background
• Advanced skills in Excel and PowerPoint
• Inquisitive, enthusiastic and diligent, and capable of challenging peers
• Strong verbal and written communication skills, with the ability to articulate complex issues clearly
• Ability to create ad hoc reporting for senior management
• Proven track record for executing on special projects / assignments, often with little lead time or information
• Highly motivated and able to thrive and think clearly under pressure and tight deadlines
• Team player with the ability to be respected as a trusted partner for the Business, Finance, and P&A Teams
• Highly motivated self-starter with excellent time management/prioritization skills
• Strong analytical and problem solving skills with ability to analyze large data sets and present conclusions concisely