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.
We draw inspiring from the flourishing workforce community of data scientists, e.g. The Information Diet.