Housing
Data Scientist - Finance (Hybrid) at Fannie Mae - Washington, DC, United States
At Fannie Mae, futures are made. The inspiring work we do makes an affordable home a reality and a difference in the lives of Americans. Every day offers compelling opportunities to modernize the nations housing finance system while being part of an inclusive team using new, emerging technologies. Here, you will help lead our industry forward, enhance your technical expertise, and make your career. As a valued colleague on our team, you will work with your team to apply fundamental techniques to support production of insights, new product or change recommendations, process improvement or automation, and predictive modeling.
- Government > Regional Government > North America Government > United States Government (0.66)
- Government > Housing (0.66)
- Banking & Finance > Real Estate (0.66)
- (2 more...)
Finance - Data Science - Associate-101193-TEMPLATE at Fannie Mae - Washington, DC, United States
GENERAL BOILERPLATE At Fannie Mae, futures are made. The inspiring work we do makes an affordable home a reality and a difference in the lives of Americans. Every day offers compelling opportunities to impact the future of the housing industry while being part of an inclusive team thriving in an energizing environment. Here, you will help lead our industry forward and make your career. CORPORATE PROFESSIONAL At Fannie Mae, futures are made.
- Banking & Finance > Real Estate (1.00)
- Government > Regional Government > North America Government > United States Government (0.88)
- Government > Housing (0.88)
- Banking & Finance > Loans > Mortgages (0.88)
AI Weekly: Algorithmic discrimination highlights the need for regulation
The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. This week, a piece from The Makeup uncovered biases in U.S. mortgage-approval algorithms that lead lenders to turn down people of color more often than white applicants. A decisioning model called Classic FICO didn't consider everyday payments -- like on-time rent and utility checks, among others -- and instead rewarded traditional credit, to which Black, Native American, Asian, and Latino Americans have less access than white Americans. The findings aren't revelatory: back in 2018, researchers at the University of California, Berkeley found that mortgage lenders charge higher interest rates to these borrowers compared to white borrowers with comparable credit scores. But they do point to the challenges in regulating companies that riskily embrace AI for decision-making, particularly in industries with the potential to inflict real-world harms.
- North America > United States > California > Alameda County > Berkeley (0.25)
- Asia > China (0.16)
- North America > United States > New York (0.05)
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- Law > Statutes (1.00)
- Government > Regional Government > North America Government > United States Government (1.00)
- Government > Housing (0.73)
- (3 more...)