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

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, …

Improving Data Quality: Anomaly Detection Made Simple

From business managers, to data scientists, to UX developers — anyone who works with data knows anomalies can be a chore to find and an even bigger chore to resolve. Incorrect or faulty data can cause a business to miss revenue opportunities or potentially make poor business decisions based on …

AI vs Machine Learning: What’s the Difference?

Artificial intelligence, or “AI”, is a buzzword that has been around for decades… but what does it really mean? For most people, it can be hard to differentiate between the futuristic sounding AI and its less glamorous sounding counterpart, machine learning, sometimes called “ML”. AI vs Machine Learning: What’s the …