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5 Trends to Watch Out in Data Science and Machine Learning Career

5 Trends to Watch Out in Data Science and Machine Learning Career

In the current scenario, we all know that data science and machine learning skills are very important to survive and thrive. But there is also a possibility of missing out on some important things because of the buzz around these technologies. Some people just try to follow the trend without paying proper attention to market trends. This results in increasing the mismatch between acquired and required skills. Knowing about the main trends that are currently shaping the data science and machine learning landscape will help you identify the right skills where you need to invest your time and effort. So, let’s check out the top 5 data science and machine learning career trends for 2020.

1. Required Specializations by the Companies

Data Scientist and Machine Learning Engineer are fascinating job titles, but they are not sufficient as companies are looking for specializations within these fields. The companies prefer to hire professionals who are skilled in the technology they are using.

2. Increased Demand for Data Engineers

Recent surveys have shown that the demand for data engineers exceeds the demand for data scientists. Previously, the companies used to hire data scientists relentlessly. But now they don’t have enough resources to provide their data scientists and this makes data engineering one of the most prominent digital skills to have in 2020.

3. Reduced Number of AIOps Engineers

The high number of data scientists has triggered the demand of engineers at the deployment end (AIOPs). The industry has enough resources for training models. But every model needs regular data and model versioning at the deployment end to ensure that the model meets the dynamic demand of businesses. And this is where the industry needs AIOps. This is the reason that the area currently has a huge opportunity.

4. Python Is New Age Language

Python is the way to go when it comes to machine learning and data science because it has the packages specifically designed for these jobs. For beginners, the trouble is that they have to learn and understand the language because it is typical at the same time. Most of the e-learning websites have only a few contents of Python tutorials based on Data Science and Machine Learning.

5. The portfolio is a must thing

This is a tricky part for someone looking forward to starting their career in this field. 

Online portals like GitHub and Kaggle offer you the platform to showcase your work whether you have worked on it individually or with a team. The employer also asks you for GitHub and Kaggle profiles in the present scenario. So, be ready with them as will help you showcase your skills.

You must have understood by now that with the increasing demand for professionals the competition also increases. For tech-savvy professionals, it means loads of new career opportunities and new horizons of possibilities. But to take advantage of this dynamism, professionals need to update with all the trends in the technologies. This field is filled with a lot of career opportunities. There is a huge demand for professionals who are skilled in working in this field. If you have knowledge of all the things related to this field then you can easily grab the attention of your dream employer. HR professionals always look for skilled professionals and they always get a better salary than the less-skilled ones. You can go for a certification in Data Science. If you have a certification relevant to your field of job then your resume speaks for you. There are various certifications available that can solve your purpose. So, don’t waste your time to launch your career in this field.