Data Science
We are working on several data science projects that will either be licensed or open-sourced depending on the valuation phase for commercial application:
Product viability score based on sentiment algorithm
Mobile trending algorithm built on Twitter's Fabric API
Zero to One: Helping answer the question: "what is no one working on?" based on programmatic media queries
Churn prediction models
Story of leveraging machine learning to predict—and reduce—churn (SaaS terminology for when a customer leaves). Our approach pitted two ML models against each other: XGBoost vs. Random Forest. The latter emerged victorious, and the model output (csv file from a Python notebook in Mode) was integrated both technically (Salesforce) and operationally (via weekly Red Account meeting) for the Clearbit Customer Success team.
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We draw inspiring from the flourishing workforce community of data scientists, e.g. The Information Diet.