Strategic Analytics Manager-Vice President at JPMorgan Chase, Jersey City, NJ
Strategic Analytics Manager-Vice President at JPMorgan Chase in Jersey City, NJ. Est. up to $200k. Apply with swipeandhired.
Are you passionate about applying data science and AI to optimize processes and shape customer experience at scale? If you enjoy solving business problems analytically, using AI in your day-to-day work, and influencing strategy for a critical line of business, this role is for you.
As a Strategic Analytics Manager in Data & Analytics supporting Home Lending Operations, you’ll help build an automated, AI-centric Home Lending business that deepens relationships with our more than 70 million Chase households.
You’ll apply AI in everyday analysis to support key business decisions, and bring the curiosity to identify, prototype, and scale new agentic use cases that improve operational processes and customer outcomes. You're an avid learner, eager to use data science and AI to launch and evolve the top priorities in Home Lending Operations.
Job Responsibilities:
- Partner with Operations, Product, Technology, Finance, and Strategy teams on key Home Lending Operations initiatives and decisions – product performance, customer outcomes, and operational efficiency.
- Build, lead, and develop a high-performing analytics team – setting direction, managing day-to-day prioritization, providing coaching and career development, and fostering a culture of rigor and curiosity.
- Own analytics delivery end to end – problem framing, measurement design, data exploration, analysis, and clear recommendations to senior stakeholders.
- Anticipate the questions leaders will ask, such as risks, tradeoffs, and edge cases, and answer them in the first version of the work. Ask ‘why, ’ challenge weak logic, and drive work to a conclusion.
- Set analytics quality standards for the team – documentation, peer review, and reproducibility – and maintain strong controls around data accuracy and results.
- Define requirements for foundational data tables to support analysis, partnering with Data/Technology teams to align with data strategy.
- Develop always-on reporting with key metrics and trending. Partner with the Business Intelligence team to deploy dashboards to production.
- Set up day-one measurements for new product releases, including reporting on key metrics, evaluating data quality, and experiment design (including A/B testing).
- Identify and develop high-value AI and machine learning use cases for HL Operations that automate/optimize processes and support digital customer experiences. Partner with the Modeling team to take use cases through governance.
Required qualifications, capabilities, and skills:
- Quantitative bachelor’s or advanced degree (e.g., Computer Science, Engineering, Operations Research, Statistics, Economics, Math, Physics)
- 7+ years of experience in analytics roles
- 3+ years of people-management experience leading analytics teams, including hiring, coaching, and performance development
- AI fluency – you use AI tools in day-to-day analysis to work faster and produce better solutions
- Experience translating ambiguous business questions into structured analytical approaches and actionable recommendations, and sound judgment on what is good enough versus needs deeper work
- Skilled in data querying, transformation, and analysis using modern analytical tools and programming languages (Python and SQL)
- Strong data storytelling capabilities, including simplifying complex concepts for audiences of varying levels across business and technical functions, with experience presenting analytical insights and recommendations to senior leaders
- Strong commitment to iterative development and measurable outcomes, with the ability to incorporate stakeholder and customer feedback
- Work effectively across cross-functional teams – aligning stakeholders and delivering high-quality work by drawing on the team’s complementary strengths
- Proficient with data visualization tools such as Tableau
Preferred qualifications, capabilities, and skills:
- Banking or similar industry experience, especially Home Lending
- Experience with experimental design (including A/B testing) and other statistical measurement methods
- Experience developing, testing, or scaling AI-enabled and agentic use cases in business workflows