What is it like to be a DATA SCIENTIST in 2021?

Data science is booming in 2021.

To take advantage of this opportunity, enroll in our data science course in Delhi with placement now.

Job Outlook in 2021

Things have changed over the last couple of years. With the creation of machine learning libraries that abstract much of the ambiguity behind the algorithms, and a recognition that it takes a range of skills that are not typically learned by academic research alone and that it is needed to practically apply machine learning to solve business problems.

Based on their ability to conduct applied data science rather than just analysis, businesses are now hiring data scientists. Applied data science requires a very realistic skillset that brings value to an organization in the shortest possible period. In addition, as more businesses move their data and machine learning solutions to the cloud, an understanding of the latest techniques and technologies related to this is becoming paramount for data scientists.

In addition, we agree that we are largely behind the days of a data scientist focusing strictly on data modeling, using data pulled together by data engineers, and then handing the concept over to a team of software engineers to bring into production. In most industries, with the exception of some of the very major tech players, the resources in those teams are either not available or there is no alignment of goals at the right time.

Data Science job estimates as per the occupational outlook handbook

• 15% increase from 2019 to 2029
• 2019 employment: approximately 32,700 positions
• 2029 employment: approximately 37,700 positions

As you can see, for the planned work, the numerical increase is 5,000. Data scientists can also fall into other job categories, such as software engineering and statistics, along with computer and information research sciences, which are also seeing growth. It is important to note that the projected growth rate for all occupations is higher than the average, which is 4 percent.

In fact, the growth rate is estimated at 31 percent, one of the highest in the United States, specifically for data scientists and other mathematical science careers.

Opportunities and Pay that Data Scientists can expect in 2021

The year 2020 notwithstanding, the pay for a data scientist or a computer and information research scientist is somewhat independent. There are a lot of statistics on these standards for salaries. However, it is important to evaluate what position you are specifically applying for or seeking, even with the data provided, and to examine reasonable wage requirements at your next or even current workplace.

India has created the demand to hire about 50,000 data scientists for 2020 and 2021 as the second-highest country next to the US. The average salary in the Indian market for a Data Scientist with less than a year of experience is around 7 LPA.

Also, start-ups do not shy away from providing up to 5 LPAs with zero real-time expertise to a well-trained data scientist. Mid-Level – 3 to 5 years of experience between 10 LPA – 14 LPA can be easily obtained in a salaried job. While we can now assume that data scientists have been around for quite a while, in job descriptions from different businesses it seems to be normal that the need is still there and the outlook is even more optimistic.

The most sought after Indian MNCs with data science job openings along with their average annual salary

• Accenture: Rs 6.3 Lac per annum
• Capgemini: Rs 7 Lac per annum
• Myntra: Rs 8 Lac per annum
• IBM: Rs 4.7 Lac per annum

HealthCare would create around 20,000 job opportunities for the industry alone. By the end of 2020, the Automotive sector looks forward to generating at least 5000 jobs. Development of software, which alone will generate nearly 1 lakh of job opportunities, is the most important. Globally, there are around 2,50,000 plus e-commerce businesses, so it is obvious that there is a massive demand for data scientists as these businesses analyze huge quantities of data per day.

Key Skills

1. Airflow – Many organizations are increasingly adopting Apache Airflow, an open source workflow management platform, for the operation of ETL processes and machine learning pipelines. Many big tech companies such as Google and Slack are using it, and on top of this project, Google has also developed their cloud composer app.

2. Software Engineering – Traditionally, data science code is chaotic, not always well checked, and lacks adherence to styling standards. This is good for initial data exploration and fast analysis, but a data scientist would need to have a good understanding of software engineering concepts when it comes to bringing machine learning models into production.

3. Python 3 – As support for Python 2 was removed by most libraries on 1 January 2020, Python 3 (the new edition) has now firmly become the default language version for most applications. If you are now studying Python for data science, choosing a course that works with this version is vital. You will need a clear understanding of the language’s basic syntax and how functions, loops, and modules can be written. Be familiar with Python object-oriented as well as functional programming, and be able to design, run and debug programs.

4. SQL and NoSQL – The vast majority of organizations use relational databases as their analytical data warehouses, and SQL is the tool that can provide you with this knowledge as a data scientist. NoSQL (‘not just SQL’) is a database that does not store data as relational tables, but stores data as key-value pairs, wide-columns, or graphs instead. Google Cloud Bigtable and Amazon DynamoDB provide examples of NoSQL databases.

As the amount of data generated by businesses grows and unstructured information is used more frequently in machine learning models, organizations shift to NoSQL databases either as a supplement or as an alternative to the conventional data warehouse.

Conclusion 

In 2021, Data Science will have a new landscape with multiple opportunities. In addition to a competitive wage, along with the advantages of working from home, you can also expect key advancements in the industry.

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