Lead Solutions Engineer, Financial Forecasting & Analytics - Vice President

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorgan Chase & Co. seeks a Lead Solutions Engineer in the Financial Analysis Data Science Center of Excellence to own the end-to-end macroeconomic forecast generation and distribution, modernize the operating model, and ensure production-ready, auditable solutions.

You will translate complex requirements into engineered solutions with clear controls and documentation, and collaborate across governance and technology teams.

Qualifications

• Master’s degree (or equivalent) in Computer Science, Data Science, Quantitative Finance, or a related field

Responsibilities

• Own the end-to-end macroeconomic variable forecast generation and distribution process
• Architect and implement automation that replaces manual steps with governed workflows
• Translate complex business requirements into scalable engineering solutions with clear controls and documentation
• Lead solution design and systems integration across data sources, platforms, and downstream consumers
• Advance AI/ML-enabled forecasting initiatives from concept through production adoption
• Lead and develop a global team of engineers and data analysts

Job description

Help shape how business-critical macroeconomic forecasts are generated, controlled, and delivered across the firm. You will modernize a complex forecasting workflow and build resilient production solutions that improve transparency, auditability, and scalability. You will partner closely across Finance, Technology, Transformation, and Governance to deliver outcomes that are durable, well-controlled, and ready for enterprise use.

Job summary

As aLead Solutions Engineerin theFinancial Analysis Data Science Center of Excellence, you will own the end-to-end macroeconomic variable forecast generation and distribution process and modernize it into a reliable, controlled operating model. You will translate complex business requirements into well-engineered solutions with clear controls, documentation, and production support standards. You will collaborate across teams to align architecture, governance, and delivery outcomes. You will lead and develop a global team while remaining technically engaged in architecture and engineering decisions. You will also contribute to advancing artificial intelligence and machine learning-based forecasting and analytics capabilities.

Job responsibilities

• Own the implementation and successful execution of the end-to-end macroeconomic variable forecast generation and distribution process
• Architect and implement automation that replaces manual and offline steps with governed, auditable workflows
• Translate complex business requirements into scalable, maintainable engineering solutions with clear controls and documentation
• Lead solution design and systems integration across data sources, platforms, and downstream consumers
• Advance artificial intelligence and machine learning-enabled productivity and forecasting initiatives from concept through production adoption
• Lead and develop a global team of engineers and data analysts through hands-on mentorship, standards-setting, and talent development

Required qualifications, capabilities, and skills

• Master’s degree (or equivalent) in Computer Science, Data Science, Quantitative Finance, or a related field
• At least eight years of experience in engineering, data or platform delivery, analytics enablement, or technology roles in a large, complex organization
• Demonstrated ownership of full software delivery life cycles from requirements through release and ongoing production support
• Proven ability to design, architect, integrate, and implement end-to-end solutions across multiple systems and platforms
• Strong programming and scripting skills (for example, Python and Microsoft Excel)
• Experience with modern data platforms (for example, Databricks), cloud environments (for example, Amazon Web Services), and software delivery tooling (for example, continuous integration and continuous delivery pipelines)
• Data querying and data engineering skills (for example, Structured Query Language)
• Experience delivering artificial intelligence and machine learning-based solutions in an enterprise environment
• Demonstrated people leadership experience, including coaching, performance support, and delivering outcomes through others across multiple locations
• Strong stakeholder management skills with the ability to drive alignment and execution across Finance, Technology, Transformation, and Governance teams