As a Lead Solutions Engineer in the Financial 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

• Masters 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

 

Modernize macroeconomic forecasting workflows with strong controls, transparency, and scalable delivery.