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 Get the Most Out of Jupyter Notebook

Jupyter Notebook has become the de facto standard for data analysis. An acronym of the three main coding languages it supports: Julia, Python, and R, Jupyter Notebook provides a user-friendly integrated development environment (IDE) and has been evolving over time to become a go-to tool for data scientists. How to …

What Companies Look for When Hiring Data Scientists

Hiring in data science has become very competitive for both companies and professionals in recent years. Fueled by the Great Reshuffle, data science positions are in high demand which can greatly benefit new and seasoned data science professionals alike. But in order to get hired in such a competitive landscape, …

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 …