BMO - Business Analyst (Financial/Banking)
Role: Business Analyst
Location: Chicago/Naperville (onsite 2 days a week)
Duration: 24 Months+ extension/conversion
Structure: W2 contract (no C2C or H1 sponsor)
Start Date: ASAP
Interview Process: 1 round virtual
Compensation: $105,000 - $140,000
Benefits: Medical, Dental, Vision, 401K, Equipment ect.
*Must have previous Business Analyst experience working within banking or financial institutions in wealth AND background in AI *
Must Haves:
- Local to Naperville, IL and willing to be onsite 2 days per week
- Strong core Business Analyst experience with end‐to‐end requirements gathering
- Prior experience supporting wealth management initiatives
- Experience working on AI, machine learning, or advanced analytics projects
- Ability to investigate, identify, and document data sources across enterprise systems
- Experience translating business needs into high‐level and detailed requirements (LRDs / waterfall documentation)
- Comfortable working in a waterfall delivery model
- Ability to partner closely with business stakeholders to define use cases and success criteria
- Strong communication skills and ability to interface with both business and technical teams
- Ability to support multiple machine learning projects simultaneously
- Experience working under senior leadership
Nice to Haves:
- Prior experience within large financial institutions or enterprise banking environments
- Experience supporting Gen AI use cases in wealth management
- Familiarity with customer data, wealth data, and financial datasets
- Experience collaborating with data engineers and data science teams
- Understanding of personas, access controls, and governance in AI initiatives
- Experience helping structure ambiguous or "random" AI use cases into clear requirements
Day to Day:
- Sit onsite in Naperville 2 days per week and collaborate closely with business and technical teams
- Partner with wealth management stakeholders to understand business problems and AI use cases
- Investigate where required data lives and identify relevant data sources for machine learning models
- Convert business requests (e.g., "do XYZ with this data") into structured, high‐level requirements
- Create and maintain LRDs and other waterfall requirements documentation
- Work closely with data engineers, who will handle data builds and pipelines
- Support multiple ongoing machine learning and AI initiatives focused on wealth use cases
- Help define success criteria, personas, and access needs for Gen AI projects
- Ensure requirements are clear, actionable, and aligned with business priorities
- Act as a strong core BA, without expectations around ETL development or dashboard buildouts