AI-Driven Investment Data Analyst

RBC; Minneapolis (MN); On-site; USD 70,000 - 130,000; Full time

Job summary

RBC is seeking a Senior Data Analyst focused on Investment Insights within its U.S. Global Asset Management division. The role bridges North American investment teams and global data capabilities, driving data excellence and adoption of new tools across US offices.

You will translate investment challenges into data solutions, leading initiatives from data ownership to process documentation and automation, with a strong emphasis on fixed income data workflows.

Qualifications

• Bachelor’s degree preferably with a focus in finance, economics or business.
• 2-5 years of investment management data & reporting experience, preferably with experience with fixed income funds.
• Experience leveraging Python and/or SQL for data management/extraction.
• Able to work independently with remote management structure.

Responsibilities

• Identify opportunities for improving processes, tools, and services that support investment operations.
• Execute and implement opportunities using available tools and technologies.
• Contribute thought leadership on how technology can multiply investment team effectiveness.
• Build business cases for strategic data initiatives based on stakeholder feedback.
• Explore AI-driven productivity enhancements for investment data workflows.
• Champion adoption of self-service data applications across North American teams.
• Deliver training and hands-on support to investment professionals.

Skills

Investment data knowledge

Independent work

Data storytelling

Critical thinking

Education

Bachelor's degree in Finance, Economics, or Business

Tools

Python

SQL

Tableau

Power BI

Job description

RBC is seeking a Senior Data Analyst focused on Investment Insights within its U.S. Global Asset Management division. The role bridges North American investment teams and global data capabilities, driving data excellence and adoption of new tools across US offices.

You will translate investment challenges into data solutions, leading initiatives from data ownership to process documentation and automation, with a strong emphasis on fixed income data workflows.