About this role
Help shape how business-critical macroeconomic forecasts are generated, controlled, and delivered across the firm. In this role, you will modernize a complex forecasting workflow. You’ll partner closely with Finance, Technology, Transformation, and Governance teams to deliver resilient production solutions and lead a global team while staying hands-on in architecture and engineering.
As a Lead Solutions Engineer in Financial Analysis Data Science Center of Excellence, you will own the end-to-end macroeconomic variables forecast generation and distribution process and modernize it into a reliable, controlled operating process. You’ll translate complex business requirements into well-engineered solutions that improve transparency, auditability, and scalability. You will collaborate across teams to align architecture, governance, and delivery outcomes. You will lead and develop a global team while remaining technically engaged. You will also contribute to advancing AI/ML-based forecasting and analytics capabilities.
Job responsibilities
- Own the implementation and successful execution of the end-to-end MEV generation and distribution process.
- Architect and implement automation to replace 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 AI/ML-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
- 8+ 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 lifecycles 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 advanced MS Excel)
- Experience with modern data platforms (e.g., Databricks), cloud environments (e.g., AWS), and SDLC tooling (e.g., CI/CD).
- Data querying and data engineering skills (e.g., SQL)
- Experience delivering AI/ML-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