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. As a valued colleague on our team, you will contribute to planning and implementing all aspects of content marketing in the consumer journey, as well as drive brand and business value with great digital experience design and content.

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.

Summary: Whether you are a startup person or data science-minded executive in a larger organization what logic can you apply to spot the most compelling opportunities for AI in your organization. In 2014 Kevin Kelly, founder of Wired magazine and prolific futurist famously said, "The business plans of the next 10,000 startups are easy to forecast: Take X and add AI." Kevin you were clearly right. The Silicon Valley and every other tech startup haven are awash in companies trying to fulfill his vision. However, whether you are a startup person or data science-minded executive in a larger organization that's not enough information to spot compelling opportunities. What are the rules or guidelines you can apply to identify these transformative applications?

Machine learning is a budding branch of artificial intelligence (AI) that has become all the rage, and industry after industry is climbing on board this ongoing trend. The biggest and brightest minds have become increasingly enthusiastic about the societal and business applications for this emerging technology. Some of the stock market's biggest companies are using the technology to improve performance and gain a competitive edge. While the market potential for machine learning is massive, there is no consensus on just how big it could eventually be. The global machine learning market is forecast to grow to $8.81 billion in 2022, producing a compound annual growth rate of 44%, according to a report by MarketsandMarkets Research.

Summary: Whether you are a startup person or data science-minded executive in a larger organization what logic can you apply to spot the most compelling opportunities for AI in your organization. In 2014 Kevin Kelly, founder of Wired magazine and prolific futurist famously said, "The business plans of the next 10,000 startups are easy to forecast: Take X and add AI." Kevin you were clearly right. The Silicon Valley and every other tech startup haven are awash in companies trying to fulfill his vision. However, whether you are a startup person or data science-minded executive in a larger organization that's not enough information to spot compelling opportunities. What are the rules or guidelines you can apply to identify these transformative applications?

Summary: Whether you are a startup person or data science-minded executive in a larger organization what logic can you apply to spot the most compelling opportunities for AI in your organization. In 2014 Kevin Kelly, founder of Wired magazine and prolific futurist famously said, "The business plans of the next 10,000 startups are easy to forecast: Take X and add AI." Kevin you were clearly right. The Silicon Valley and every other tech startup haven are awash in companies trying to fulfill his vision. However, whether you are a startup person or data science-minded executive in a larger organization that's not enough information to spot compelling opportunities. What are the rules or guidelines you can apply to identify these transformative applications?

Summary: Whether you are a startup person or data science-minded executive in a larger organization what logic can you apply to spot the most compelling opportunities for AI in your organization. In 2014 Kevin Kelly, founder of Wired magazine and prolific futurist famously said, "The business plans of the next 10,000 startups are easy to forecast: Take X and add AI." Kevin you were clearly right. The Silicon Valley and every other tech startup haven are awash in companies trying to fulfill his vision. However, whether you are a startup person or data science-minded executive in a larger organization that's not enough information to spot compelling opportunities. What are the rules or guidelines you can apply to identify these transformative applications?