SDS 561: Engineering Data APIs

In this episode, Ribbon Health CTO Nate Fox joins us to discuss the ins and outs of APIs. Tune in to hear him share how he and his team build out APIs from scratch; how they ensure the uptime and reliability of APIs and how they leverage machine learning to improve the quality of healthcare delivery and maximize their social impact. In this episode you will learn: • What are APIs? [13:20] • How Ribbon Health’s data API leverages ML models to improve the quality of healthcare delivery [16:08] • How to design a data API from scratch [20:00] • How to ensure the uptime and reliability of APIs [25:28] • How Ribbon uses knowledge graphs, manually labeled data samples, and an XGBoost model with hundreds of inputs to assign a confidence score [27:14] • Nate’s favorite tool for easily scaling up the impact of data science [37:40] • What is Nate’s day-to-day like? [34:34] • The qualities Nate looks for when hiring data scientists [39:50] • How scientists and engineers can make a big social impact in health technology [42:50] Additional materials: www.superdatascience.com/561

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The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.