Soft Skills: How to Avoid Getting Automated Out of Data Science
Igor Korolev, DO, PhD ??
Physician/Neuroscientist | Digital Health | Biotechnology | Brain/Mental Health | Healthcare Strategy & Innovation | Passionate about improving health via science & technology
If I had to give one piece of advice to current and aspiring data science / analytics professionals, it would be to focus on developing soft skills. Here is why.
Automated Machine Learning (AutoML) is growing in popularity and adoption in the data science community -- it's here to stay long-term (see H2O.ai, DataRobot, & Google Cloud for examples). AutoML will become an indispensable digital assistant for doing data science more efficiently -- a tool that enables next generation "augmented" data science.
Data scientists won't be replaced by AutoML, but those who use AutoML will replace those who don't.
AutoML will redefine the scope of practice, skills, and activities of data science and analytics professionals over the next few years. While many aspects of data science will become automated, humans will continue to provide domain knowledge, define problems, ask questions, and apply communication, problem solving, creativity, and critical thinking skills.
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Senior leader with extensive experience in customer insight, marketing analytics & data science ? 6 time member of Data IQ Data 100
5 年Only a small proportion of data scientists have ever been able to progress to senior levels based on technical skills alone. Sound advice for anyone entering an analytics career is that to be truly effective and to advance in most organisations then developing "softer" or consulting skills is essential. Your role will often be to provide internal consultancy and deliver projects based on how to use data to drive commercial outcomes, developing those consulting skills is key.
I write about machine learning tools and software.
5 年Robotic surgery’s been a thing for 15 years. I don’t see surgeons standing by freeway exits with signs reading “will work for food”
Sr Director - AI Product & Strategy Leader | "The greatest obstacle to discovery is not ignorance; it is the illusion of knowledge."
5 年Even more reason to continue to build your business domain and soft skills to compliment your technical skills
Wild Card - draw me for a winning hand | Creative Problem Solver in Many Roles | Manual Software QA | Project Management | Business Analysis | Auditing | Accounting |
5 年The problem is not being automated out of data science. The problem is how to GET INTO data science. There are zero entry level data science jobs that require no experience.? Recent grads and career changers are locked out.
CxO / #BoardDirectors | #Biomedical | #DataScience | #Web3 "degen" | 75+ #AI Patents | #CxO #Advisory/#Research | #SPN
5 年_Igor_, tough to replace domain expertise. AutoML explains the what nicely; not the why? and how?