A career in data science is lucrative and rewarding. But the path to starting or advancing a data science or analytics career is not always linear. Over the past decade, the availability of data and demand for data science skills and data-driven decision making has skyrocketed. Pushed further into the spotlight by the drastic shift in business operations and consumer behavior caused by the COVID-19 pandemic, analytics and data science are now cemented as essential navigational tools across industries and functions. This interesting subject came to us from The Machine Learning Times in their article, “Why AI Isn’t Going to Replace Data Scientists Any Time Soon.”

Data science is a 21st century job skill that everybody should have. Despite the hype over artificial intelligence (AI) and other emerging technologies, data scientists are needed for AI to thrive, despite its name. Why? Because most organizations have minimal knowledge of how their AI systems make the decisions they do, and as a result, how the results are being applied in the various fields that AI and machine learning are being applied. 

Explainable AI allows users to comprehend and trust the output created by machine learning algorithms. In fact, data scientists need machine learning skills to study transactional data to make valuable predictions.

Melody K. Smith

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.