Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Machine Learning Times brought this interesting information to our attention in their article, “How Can We Fix the Data Science Talent Shortage?.”
Data science enables better decision making. It allows users to define goals and identify opportunities to engagement with target audiences.
Data has become central to our lives, and data science has evolved into the main discipline to transform it into value. The discipline advances so fast that what was considered cutting edge a few months ago is obsolete now. It can be hard sometimes to keep up with the pace of development, but the data science community is very open and welcoming, even for people that don’t have a background in mathematics or computer science.
Entry-level data jobs tend to focus on working with these tools—tuning hyperparameters for machine learning models and cleaning data—rather than building and training machine learning models. Those types of roles are largely reserved for data scientists with five or more years of experience. Will this continue to work for the future?
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.