Data Scientist needs a strong quantitative background, and he/ she can excel in any given field with training. Since the heart of Data Science is, Math and Statistics. Coding knowledge gives you tools to get the work done efficiently and quickly. So, before discussing how to become a Health Data Scientist, let me briefly describe the profession. A Data Scientist in Healthcare or a Health Data Scientist is a professional who is an expert in analyzing a huge amount of data, using statistical models, mathematical formulas, coding skills, and a great level of soft skills that include problem-solving, analytical thinking, great interpersonal and communication skills, and at last sound knowledge in the healthcare department.
Now how to become one? A profession like these sprawled recently, and hence there is no fixed route to becoming a Health Data Scientist. You must be an excellent Data Scientist and then you could march your way into the medical field, to efficiently process, analyze, and extract key insights from a large number of health datasets, ranging from healthcare, bioinformatics, health economics, genomic science, clinical trials, observational studies, computational biology, patient records, etc. The path for you is to acquire a bachelor’s degree in any relevant field, (math, statistics, computer science, etc.) then get trained and probably certified by enrolling in a good Data Science course, to make you competitive with industry standards. And once you are an expert in general Data Science, you then undergo short-term training in the specific healthcare domain, that you like to work in. The tools knowledge you need to have is Programming Languages like Python, R, or SAS, any Data Visualization tool if necessary.
Many of the tools are dependent on the organization that you will be working with. So, if you wish to get started, and want to get started right away in general Data Science, watch the following YouTube video on the Data Science Online course.
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