A Framework for Building Customer Segmentation Models

If someone asked you to describe your customer base or audience, how would you do it? Would you describe a generalized persona? Perhaps a list of demographic features? Or maybe you would list several interests that align with your core mission or brand. While this might seem like an outline …

Incorporating Decision Science into Data Science

Machine Learning and mathematical rigor are tools at data scientists’ disposal. But we all know that having a better calculator won’t exactly result in better test scores, and having a more powerful computer won’t necessarily make you a better programmer. To develop a strategy that doesn’t underperform, a data scientist …

Going from MLOps Level 0 to Level 1

Evolving past local Jupyter Notebooks to Autonomous Systems: Industry Data Science has diverged into a few dominant verticals as the field has matured, but the primary specialty has been Enterprise Machine Learning (with Product-centric Data Science as a close second). Going from MLOps Level 0 to Level 1

How to Overcome Data Science Staffing Challenges

The traditional data science team has undergone a period of drastic change in the past two years due to COVID-19 and the “Great Reshuffle” that has followed. This period has witnessed relocation of staff to remote locations, changing business models in response to the pandemic, and challenges in attracting and …

How To Manage Your Team’s WFH Data Analysis Gap

One thing we’ve all learned in the last year is how to work without our colleagues being steps away. When it comes to data analysis, and specifically to measuring the impact of changes to the business, the physical distance between staff requires granting more trust and latitude down the organization, …