Top data science skills of 2021

Top data science skills of 2021 Keywords: Data science skills, data science certifications, data science career, data science jobs Ever since the role of big data was recognized in the success of businesses, there has been a continuous upsurge in demand for professionals proficient in data science. With the increase in demand for data science professionals, there has been an upsurge in jobs openings as well.

Yet… the positions go vacant. Reason: Lack of data science skills in the professionals.

So what are the data science skills that you need to master to succeed as data science professional in 2021.

Without wasting more time, let’s have a look at some of the top data science skills employers seek in professionals when they open the data science jobs in their organizations.

1.Programming languages like Python, R, and SQL are still the top three languages that are required for a successful data science career. Most of the successful data scientists will swear by Python. Reason: It is quite advanced when it comes to open- source contributions and it is easy to learn as well. SQL is another language to learn for professionals seeking work in any data science related field including data analyst, business analyst, or even data analyst.

2.In addition to programming languages, it is important to know the various upcoming Python libraries. For deep learning TensorFlow is the top in demand Python learning and its popularity is increasing at steady pace. Another strong contender is PyTorch. For machine learning scikit-learn is the popular choice, as it helps in building machine learning models. Numpy and Pandas help in the initial stages of data science process that includes cleaning and manipulating the data for insights.

When the industry experts compared the skills from 2019 to 2021, there have been a fast rise and decline in certain skills for data science jobs. Here is the list of both quick rising and declining data science skills for professionals.  There has been an upward surge in demand for skills like AWS, cloud, and Google Cloud Platform (GCP)

 There has also been an upsurge in skills related to deep learning so proficiency in TensorFlow and PyTorch is important  While R remains stagnant in terms of popularity, Python and SQL kept growing in importance over the years  There has been a steady decline in once popular Apache products like Spark, Hadoop, and Hive 3.Technical skills like Statistics and probability; Calculus and Linear Algebra, along with data visualization, data wrangling, and database management are still considered important for a successful data science career.

4.Business acumen is another important skill for data scientist. In other words, domain knowledge is a must before you venture out as a data scientist. You may like to consult industry experts in the initial stages before you develop a business sense yourself.

5.Soft skills like storytelling, facilitation, strong communication skills are still in demand and will continue to do so.

You can both acquire and hone your data science skills through various bootcamps, Kaggle, and of course going for data science certifications from reputed institutes that offer programs that prepare you to work in any professional settings. Data Science certifications will give a seal of approval on all the skills and knowledge you have acquired from various sources and build confidence in the hiring manager.