Lead Solutions Engineer, Financial Forecasting & Analytics - Vice President
Jersey City, NJ, United States
- Pay
- Pay not listedSimilar roles state $153K–$225K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingOwn end-to-end macroeconomic variable forecast generation and distribution
Automate manual, offline forecasting steps into governed, auditable workflows
Design solutions and integrate data sources, platforms, and downstream consumers
Take AI and machine learning forecasting initiatives from concept to production
Lead and mentor a global team of engineers and data analysts
From the employer’s posting
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
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
Education & alternatives
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
Tools in this posting
- Python
- Databricks
- Excel
- SQL
- AWS
Source — Tool mentions in context
- 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)
- 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 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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 30, 2026 · 29 days ago
- Recorded sightings
- 185
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
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- Ask the employer about the pay range before committing time to the process.
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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 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
- 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
Source details
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- Pay
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- Location & working pattern
Jersey City, NJ, United States
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- Work authorization
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