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Different Data Science Jobs
Meet the Author : Mr. Bharani Kumar
Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of Innodatatics Pvt Ltd and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 17 years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.
Table of Content
The most popular and in-demand area of information technology is data science. The need for data and its uses is growing along with the technological trend. Global management is moving towards digitalization. Due to the development and improvement of digital technologies, each work that was formerly performed manually is now managed digitally. The amount of data has significantly risen. In order to employ this massive amount of data, it must yield some advantages. Data scientists are those who handle data and get forth information that is useful from it. The market for data science employment has grown as a result of the data science trend's growth and its applications in all industries. To have a thorough understanding of data science jobs and its potential in the market, it is essential to be aware of the many sorts of positions that are available in the field.
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According to one report, data science jobs are leading the job market at the current time. The data science jobs available in the market are more than any other type of job. There are many institutes in India and other countries in which the vacancies of data science are more than that of available data scientists in the market. The data science career is much brighter, and there is no problem with job availability in the market. Moreover, the salaries of data scientists are much higher than that of other jobs in the market. Nowadays, jobs in the market are less in other fields. Even in information technology, the jobs of other fields of technology are less as compared to the data science field. Due to more requirements of data scientists, it is necessary to know about different types of jobs of data science in the market. Our team of experts has explained the different data science job types in detail. You will find it helpful while choosing a data science career.
Four types of Data Science Jobs
The types of data science jobs can be different is different perspectives, but our team of experts has explained the four general data science jobs in detail as follows.
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The Data Analyst
The most in-demand and necessary employment in many businesses and organisations is that of a data analyst. Every company requires a data analyst who can use the data in the organisation to execute various sorts of data analyses. Today, practically every organisation has made the switch to digital technology, and the volume of data created by the organisation is enormous. If you don't use the extensive data of a certain organisation for the good of that organisation, it will serve no use. This data may be analysed to yield a variety of insightful findings. The information that was gathered may be utilised to create a variety of practical company success tactics. Data analysis approaches may help organisations identify a variety of business-related issues. As a consequence, the organisation is able to work on various issues to identify solutions.
The data scientist should have excellent data science skills and knowledge of data science. He should also be much more familiar with the data science tools to use for the data analysis. Moreover, experience matters a lot in this job. If you want to become a data analyst, you need to have good experience in real-world data science projects. You can only increase your data science skills by working on more projects. The reason is that you will not be facing a similar type of data science problem in the specific organization. You need to have good experience with multiple types of data science projects for this job.
Additionally, you should concentrate on data science visualisations as this position necessitates data visualisation expertise. The data analyst can compare many facets of organisational and corporate data using data visualisation tools. The data scientist might draw many conclusions and insights from visualisations. Additionally, he can use various analytics on the data depending on the situation. These insights can also be predictive, meaning that data analysts can foresee certain elements of the future from the available information.
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Machine Learning Engineer
Data science is a mixture of different other fields, which include artificial intelligence, machine learning, mathematics, and statistics. Machine learning is the most important part of data science, which provides different algorithms for both prediction and classification of the data. When we apply different analytics to the given data, we mostly use the machine learning algorithms on the data set for prediction and classification purposes. Machine learning algorithms can help in predicting different types of insights and extracting some useful information from the data sets. The machine learning engineers perform different machine learning algorithms on the organization or business firm data.
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For becoming a machine learning engineer, you need to have comprehensive knowledge of different machine learning algorithms. You should also have good practical skills for all these algorithms. Moreover, you should work on different real-world problems and apply those algorithms on those problems to solve these problems.
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Data Generalist
The data scientist in this sort of particular data science position is responsible for overseeing all data science operations, including data analyst duties, data visualisation projects, and machine learning based work. You must be well-versed in the data science technologies used for data analysis, data visualisation, and machine learning in order to apply for this position. Some tools need programming to use them for data science, while others do not. There is a greater tendency in many organisations for this kind of data science career. Organisations want a person who is capable of handling all data science issues and managing the data from many angles. Small organisations just need one individual for varied data science duties, but large organisations might have several data scientists with a variety of separate data science roles.
The many job categories in the field of data science and the associated duties have been covered by our team of specialists. Please keep checking our blog for other posts about data science.
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FAQs
It’s a great time to pursue a career in Data Science. With a lot of boom in Big Data and Machine Learning, the opportunities are endless for a fresher or an experienced professional. Take advantage of this time and opportunity, build your skillset, and join the MNCs to get a solid career breakthrough. Here is a list of top MNCs where you can apply for Data Science jobs:
- IBM
- Wipro
- Apple
- Deloitte
- PwC
- Amazon
- EY
- Microsoft
Data Science jobs are already at an all-time high with numerous opportunities and advancements. It is one of the top-rated careers in the job market in the present era. With more Machine learning, Artificial Intelligence, and cloud computing concepts, the future of Data Science looks bright. Data Science is predicted to develop a whopping 22 percent between 2020 and 2030, which is three times more than any other profession. So, it is one of the best professions to make your career.
Due to the Covid-19 pandemic, working from home has become the new normal. Data Science is one of the most known professions that effectively be done from home. A survey by Burthworks suggests almost 72% of Data Science professionals prefer to work from home. But this situation differs from organization to organization and their hiring policies.
Data Science interviews are simple but tricky due to the many skill sets involved, like Problem-solving, technical knowledge, communication, etc. The bar is set high for even entry-level positions. Work on various real-life Data Science problems and be thorough with your basics to easily crack the interview. Familiarize yourself with popular data sets, coding algorithms, and relevant concepts to make a difference.
- Understand data
- Understand algorithms/Logic
- Understand programming language
- Understand Statistics
- Understand business domain
There are plenty of entry-level Data Science jobs in the market. Entry-level Data Scientists make around 5.5 lakhs per annum on average. Professionals with 1 to 4-year experience can get a hike up to 8 lakh per annum in the field of Data Science.
A Data Science job is a combination of skills and knowledge. You can do an online course in Data Science to gain a basic understanding of the system, and the certification is helpful during entry-level job interviews. But to crack a Data Science interview, one must train their soft skills personally—work on real-time projects and industry-based data sets to clear their interview quickly.
The Data Science field is worth every penny you invest in it. PG courses in Data Science are from 6 months to 2 years, depending on the institute. These courses can be both offline and online. These courses are the only way to understand this vast field for a specific duration. Getting a Data Science job is only possible with a proper mentor or certification.
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360DigiTMG - Data Science, IR 4.0, AI, Machine Learning Training in Malaysia
Level 16, 1 Sentral, Jalan Stesen Sentral 5, Kuala Lumpur Sentral, 50470 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia
+60 19-383 1378
