Ingram Micro Inc.
Associate Professional, Financial Solutions Rep
Buffalo, NY, United States of America · Mid
Stay score
odds of building a lasting career here
Thin sponsorship signal and lottery-bound (~15% per draw). A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Green-card follow-through: 62%
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- 2+ years of position specific work experience within the finance and/or leasing industry.
Responsibilities
- Partner with Business Development and Solutions Development teams to support finance and leasing transactions.
- Manage financing transactions from contract execution through funding completion.
- Generate and analyze reports to support operational performance and transaction tracking.
- Perform administrative and portfolio management activities associated with transaction processing.
- Proven ability to manage multiple priorities in a high-volume environment.
Requirements
- Proficiency with Microsoft Office applications, including Word, Excel, and PowerPoint, as well as web-based business platforms.
Skills
- Strong analytical, problem-solving, and critical-thinking skills.
- Exceptional organizational skills with a proactive approach to work.
Compensation
- The typical base pay range for this role across the U.S. is USD $49,500.00 - $79,200.00 per year.
Benefits
- Bachelor's degree or an equivalent combination of education and experience required.
This listing is sourced directly from Ingram Micro Inc.'s careers page and normalized into a canonical job model.