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Actionable and Interpretable Predictions from a Stacked Model

Austen Head Austen Head | Senior Data Scientist | Quid

We predict who is likely to be interested in purchasing from our clients' sales teams, along with actionable reasons describing why we made that prediction. Some specific challenges involved in this are:
* data ingestion from a variety of external sources
* entity resolution based on low-signal keys
* recommendations of people who are likely interested in speaking to and purchasing from our clients' sales teams in the next month

Austen Head
Austen Head
Senior Data Scientist | Quid

Austen is a senior data scientist at Quid and a data science advisor at Halo and at Patreon. Previously, Austen received a PhD in Statistics from Stanford, was the first employee at the consumer fintech company Earnest, and then was an early employee at the enterprise biotech sales company Halo. His work has focused on developing data products from complex data structures which are highly understandable by non-data-savvy users

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