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Business Strategy - Machine Learning - Intelligence Operations
Chicago, IL, United States, US
·
On-site
·
Full-time
·
2w ago
As a Vice President, you will lead strategic initiatives that drive innovation and operational excellence. This is an opportunity to work with cutting-edge technology and collaborate with talented professionals across the firm. You’ll play a key role in transforming how we deliver value to our customers and the business. Grow your career while making a meaningful impact on the future of banking.
As a Vice President in Machine Learning & Intelligence Operations within Consumer and Community Banking Operations, you will lead business management and strategy efforts focused on AI/ML transformation. You will break down barriers to deliver on strategic priorities, ensure organizational alignment, and research new ways to leverage advanced technologies. Working closely with cross-functional teams, you’ll drive initiatives that improve operational efficiency and customer experience. You’ll foster a culture of excellence and innovation, supporting both team and firmwide goals. Your work will directly impact the direction and success of our AI and data strategy.
Job Responsibilities
- Manage high-priority strategy projects to address complex problems at the forefront of AI in financial services.
- Monitor and analyze industry trends, applying leading practices to refine the Consumer and Community Banking Operations AI and data strategy.
- Lead strategy project teams and collaborate with stakeholders across functions to drive alignment and deliver results.
- Support business management functions including communication strategies, financial planning, and vendor management.
- Provide coaching to strategy team members and foster a culture of excellence and innovation.
- Collaborate with cross-functional teams to identify and prioritize initiatives that drive operational efficiencies.
- Develop and deliver executive-level strategy documents and analyses that articulate the value and impact of AI and data priorities.
Required Qualifications, Capabilities, and Skills
- Minimum of 5 years of strategy experience from consulting firms or internal strategy groups.
- Outstanding ability to analyze problems and apply quantitative, analytical, and conceptual problem-solving approaches.
- Excellent oral and written communication skills, with ability to develop high-quality strategy deliverables.
- Strong relationship-building and interpersonal skills, with ability to collaborate across functions.
- Proven experience in leading strategy engagements and coaching team members.
- Familiarity with AI and data, with ability to engage stakeholders on complex technical concepts and generate executive insights.
Preferred Qualifications, Capabilities, and Skills
- Undergraduate or graduate degree in economics, finance, math, engineering, computing, or a related analytical field.
- Experience in financial services across consumer and business banking, wealth and asset management, or corporate and investment banking.
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About JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase is a multinational investment bank and financial services company that provides banking, investment, and asset management services globally. It is one of the largest banks in the United States by assets and market capitalization.
300,000+
Employees
New York City
Headquarters
Reviews
4.2
10 reviews
Work Life Balance
4.2
Compensation
4.3
Culture
4.5
Career
4.4
Management
4.1
75%
Recommend to a Friend
Pros
Good pay and benefits
Work-life balance
Career advancement opportunities
Cons
Heavy workload at times
Career advancement takes time
Pay could be better in some roles
Salary Ranges
47 data points
Mid/L4
Senior/L5
Mid/L4 · Applied AI ML Associate
2 reports
$188,500
total / year
Base
$145,000
Stock
-
Bonus
-
$182,000
$195,000
Interview Experience
4 interviews
Difficulty
2.8
/ 5
Duration
14-28 weeks
Interview Process
1
Application Review
2
HireVue Video Interview
3
Technical/Behavioral Assessment
4
Final Interview Round
5
Offer Decision
Common Questions
Behavioral/STAR
Technical Knowledge
Past Experience
Culture Fit
Case Study
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