AI Product Analyst for Fundamental Equities

Referment; Denver (CO); Presencial; USD 90.000 - 130.000; Tempo integral

Resumo da vaga

Referment is partnering with a global investment and technology firm in Denver to identify an AI product analyst for a fundamental equities team. You will work closely with analysts and portfolio managers to uncover bottlenecks, prototype AI-powered tools, and integrate new workflows that enhance research efficiency.

The role emphasizes building practical, compliant solutions, maintaining models, and sharing best practices to improve AI fluency within a data‑driven investment process.

Qualificações

• A bachelor’s degree and hands‑on experience building functional prototypes with agentic AI tools.
• Ability to read, modify, and debug code, with comfort using APIs, data feeds, and Python.
• Understanding of fundamental investment research, including financial models, thesis development, and monitoring.
• A strong product mindset and ability to operate independently amid ambiguity.
• Experience with financial-data platforms or internal automation is useful.

Responsabilidades

• Map investment-research processes and identify repetitive or high-friction work.
• Redesign workflows using agentic AI tools and rapid prototyping.
• Build and deploy lightweight AI-powered solutions, then iterate from user feedback.
• Document successful workflows and share practices that improve AI fluency.
• Ensure tools respect data licensing, information barriers, and compliance requirements.

Conhecimentos

Product mindset

Independent work

Communication

Formação

Bachelor's degree

Ferramentas

Python

APIs

Descrição da vaga

Referment is partnering with a global investment and technology firm in Denver to identify an AI product analyst for a fundamental equities team. You will work closely with analysts and portfolio managers to uncover bottlenecks, prototype AI-powered tools, and integrate new workflows that enhance research efficiency.

The role emphasizes building practical, compliant solutions, maintaining models, and sharing best practices to improve AI fluency within a data‑driven investment process.