Decision Science Vice President – Finance Analytics

Join a collaborative team of product, analytics, and engineering experts building models and tools that improve strategic finance decisions. You will work on high-impact problems, partner closely with stakeholders, and help turn data into measurable outcomes. This is an opportunity to grow your analytics and machine learning skills while delivering capabilities used across the business. As a Decision Science Vice President at JPMorganChase within the Finance Decision Optimization team, you will support the end-to-end model development lifecycle—from exploratory analysis to model testing to ongoing performance monitoring and verification of production processes. You will translate business needs into technical requirements and prototype solutions, partner closely with modeling and technology teams, and deliver analytics that drive measurable business outcomes in a fast-paced environment. You will develop a strong understanding of how finance teams use data and models to make decisions, and you will help ensure solutions perform as intended in production. Job responsibilities Drive business outcomes and decision-making through data and analytics by using enterprise data to inform modeling approaches, understand behavioral patterns, and perform sensitivity analysis Build deep knowledge of supported business areas to deliver pragmatic, effective solutions Translate business needs into technical requirements and collaborate with technology teams to deliver capabilities end-to-end Partner with end users and data product owners during user acceptance testing to confirm delivered functionality meets requirements Partner with quantitative modeling teams to develop and refine statistical models, continuously evaluating performance and effectiveness Validate that production results comply with business requirements and expected outcomes, and support ongoing monitoring and verification of production processes Design and optimize complex Structured Query Language (SQL) queries and Python scripts to support data validation and exploration, and prototype solutions for new requests and enhancements Required qualifications, capabilities and skills Formal training or certification on software engineering concepts and 3+ years applied experience 3+ years of experience at a financial institution or consulting firm in corporate finance, banking, treasury, data analytics, or quantitative modeling Strong analytical skills with demonstrated ability to collect, organize, and analyze significant amounts of information with attention to detail and accuracy Experience with statistical and experimental techniques such as controlled testing (A/B testing) Proficiency in analytics and programming tools to drive business outcomes, including Structured Query Language (SQL) and Python Strong problem-solving, critical thinking, communication, and organizational skills, with the ability to articulate options and results to senior stakeholders Ability to collaborate effectively with technical partners (including data engineering and quantitative modeling) and translate data into concise, actionable recommendations Preferred qualifications, capabilities and skills Experience supporting large-scale data projects Proficiency with additional analytics tools such as SAS or R Experience with Databricks, Streamlit, and Amazon Web Services cloud environments Experience driving adoption of artificial intelligence and machine learning solutions, including stakeholder enablement and change management