Preparing for the Economic Headwinds Created by the Coronavirus
Coronavirus disease 2019 (COVID-19) has caused plenty of uncertainty across the country and around the world. While articles and checklists abound on how to prepare…
3 Principles of Stakeholder Management for Data Scientists
As a data scientist, you might evaluate your own work based upon accuracy, completeness, models, or some other criterion. But, if you’re not able to…
Using R Plumber and Slack to Run Data Science Pipelines
Using R Plumber and Slack to Run Data Science Pipelines Last year I published a starter guide that explains how we used the R…
Four Principles of Data Science Ethics at Retina
Does your data science team worry about aligning your work with your values? Data science and machine learning provide new capabilities, and with those come…
Clustering Messy Time Series
When clustering data, it can be challenging to handle time series data, especially when the series have differing lengths. As part of my PhD work…
Customer Lifetime Value Migration Over Time
Customer lifetime value (CLV) is not a static metric. It changes over time—sometimes dramatically—as you observe new data about a customer. At Retina, we analyze…
Goal-Driven Customer Segmentation
Customer segmentation is a powerful technique for understanding your customers. However, it can be tricky to successfully implement it in a business context. In this…
5 Steps to Build an Effective Data Science Team
I’ve built and run data teams at Paypal, Facebook, and now at Retina AI. In each of those roles, I’ve also been asked how to…
Data Science User Experience: Lost In Translation
If you ever get the chance to talk to a VP of Analytics or a Head of Data Science, you will find that most have…