The Most Valuable Data Scientist Skills in 2020

Data Scientist Skills in 2020

Data science is a sector that has been ranked as among the most attractive for jobs in the 21st century. This is no surprise, given the massive inflows of data into organizations of all sizes and from all sectors. This data is a huge potential source of valuable strategic insights to guide the future course of operations of organizations.

re there a lot of jobs in data science?

Yes, according to the US Bureau of Labor Statistics (BLS). The employment of all computer and information research scientists – which includes those with data scientist skills – is expected to rise by 19 percent by 2026, an increase that is much higher than the average for all professions.

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About 5,400 new jobs in data science are expected over the current decade, and according to LinkedIn, there are more than 20,000 jobs in data science in the US today. And, as per PayScale, the average salary of a data scientist in the US is USD 96,106.

What are the top core skills required?

The most important core data scientist skills, the absolute minimum needed, are as below:

• Programming in Python and/or R: These are the two most widely used programming languages in data science. While R supports statistical computing and graphics and is hence popular for more high-end work, Python is popular due to its simplicity and hence its suitability for large projects. Python is also free, open-source, works across platforms, and offers extensive library support.

• SQL: What makes this extremely valuable is the fact that insights cannot be found without underlying data to mine, and an overwhelming majority of companies predominantly maintain their data in SQL databases of some kind. The most essential skills to know here are the basics of SQL for pulling in data with filters and optimizing table joins.

• Traditional and automated machine learning: Along with traditional machine learning (ML) i.e. knowing why and how to code algorithms, a candidate must know about automated ML to use automation to cut costs and improve efficiencies. Vendors such as H20.ai and Data Robot exist in this space, and working with these helps to reduce the time for analysis and speed up production deployment.

Which additional skills are useful?

Among the advanced data scientist skills that could put a candidate ahead of others, the following are the most useful:

• Communication and presentation: It is important to present data in concise and meaningful ways, along with coding and analyzing it properly. What managers look for are insights and recommendations that can be practically applied, and these skills are essential for this purpose. Good written and verbal presentation skills help in creating dashboards and visualization reports, which make it easy to understand the insights and recommendations. It is important to think like a consultant at any level in a data science career.

• Software engineering: More than being a qualified software engineer, it is important to understand basic architecture and data flow questions to troubleshoot better and write better code that can be transitioned to production easily. Report automation and scheduler jobs help to automate repetitive tasks.

• Cloud services: Databases of most companies are now on AWS or Azure, and many are implementing their production models on the cloud too. It is thus helpful to know the basics of Docker, containers, and deploying code and models to the cloud. This is particularly handy as companies move towards automation.

• Domain expertise: Experience is valuable, but an eagerness to learn is very useful too. Someone who is new to the company or the domain must try to pick up as much as possible from senior colleagues or partners. For instance, try to learn who uses analysis results, how they are applied and save money, and how they could be speeded up without compromising on the accuracy of results.

Apart from the above core and advanced skills, a career in data science gets a definite boost by picking one of the best data science certifications. A certification is a proof of possessing the latest skills and knowledge in the field, and a certified data science professional is someone serious about a data science career and growth in the assigned role.

Sources: https://www.theworldbeast.com/data-scientist-skills.html