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Is a career in Machine Learning lucrative or not? If this question is in your mind then rethink, because PwC report says that 31% of the executives are worried about the inability to meet the demand for AI skills over the next 5 years. In this article I will put forth this topic ‘Machine Learning Career and Future Scope’
Following Pointers will be discussed in this article,
Moreover, neglecting all these ruckuses that AI/ML will steadily and inevitably take over large sectors of the workforce and will bring mass-scale unemployment, a report from the world’s leading research and advisory company, Gartner depicts that AI is expected to pave the way for close to 2.3 million jobs by the year 2020.
AI professionals, especially in the field of Machine Learning, are in very high demand, as almost every startup (based on software), as well as a large enterprise, wants to hire people who have knowledge of Machine Learning.
To be an effective weapon of mainstream business, Machine Learning has come a long way through this decade. But fortunately, it’s still far from its probable zenith and we can expect thorough progress from it in the near future too. So, if you are an AI aspirant looking to land a job in the industry, it is the best time to upskill with one of the crucial aspects of AI, named machine learning.
You may have heard about some myths around machine learning skills that “I’m bad at math, so I can’t become a machine learning professional”, “Only hardcore coders can do programming for Machine Learning, and not a novice”, “It requires a nerd mind to become a machine learning expert”, etc.
Well, all these are really myths because, with proper dedication, anyone can acquire machine learning skills. With valid efforts and dedication, you’ll not just be a machine learning engineer but will also play an important role in the creation of a utopian world.
So, let’s know the essential skills to build a career in machine learning.
Although there is no programming language dedicated to machine learning only, on comparing the characteristics of each programming language capable of doing machine learning, Python looks superior among them.
Loading & playing around data, visualizing the data, transforming inputs into a numerical matrix and even assessment, are some basic tasks which a machine learning expert would do on a day-to-day basis. No wonder, Python is capable of doing all these heavy liftings for us. Moreover, Python also has huge support for machine learning libraries.
That’s why, if you want to be a machine learning professional, knowledge of Python programming language would be a game-changer, for sure.
Machine learning is a vast field build on some complex mathematical components such as calculus, linear algebra, statistics, probability, and optimization. That’s the reason, to accelerate the learning curve of machine learning you must have basic knowledge of these complex mathematical skills.
If one wants to pursue a career in the field of machine learning, he/she should be well acquainted with standard implementations of machine learning algorithms. These algorithms, which are widely available through libraries/packages/APIs, are one of the most integral parts of Machine Learning.
Another skillset that you must carry on the journey to become a Machine Learning engineer is ‘Data Structures’. Machine Learning professionals, in their whole career, are supposed to work for solving real-world problems, that’s why they should have in-depth knowledge of data structures concepts (stacks, queues, trees, graphs, big-O notation, searching, sorting, etc.).
What would be the typical output of a machine learning engineer? Of course, at the end of the day, a machine learning engineer’s deliverable is a software. That’s the reason, in-depth knowledge of software engineering concepts and system design are essential for a promising career in Machine Learning.
What kind of job profile should you start looking for once you got the right Machine Learning skills? Let’s have a closer look at some of the most-in-demand Machine Learning job roles.
One of the most sought job profiles in the field of machine learning is a machine learning engineer. Machine learning engineer is responsible for designing and implementing machine learning algorithms to help decipher meaningful patterns from humongous amounts of data.
The main role of a Data Scientist is to collect, analyze, and interpret large amounts of unstructured data by using machine learning and predictive analysis, to derive insight and help design future strategies. Chances of getting hired as data scientist increases if someone have a good hands-on-experience working with machine learning, Big Data technology, and analytical tools.
A Data analyst delivers value to their organization by first acquiring information about a specific topic, and then interpreting as well as analyzing it, and at last present their findings in comprehensive reports. They use their skills and tools to provide competitive analysis and identify trends. Data analysts have a strong background in calculus, economics, statistics, machine learning, and programming.
One of the most in-demand Machine Learning professionals today, data architects takes care of organizations big data ecosystem. They develop, construct, test, and maintain highly scalable data management systems by using Machine Learning algorithms. After collecting data and doing batch processing, they send it for analysis to data scientist via an API.
The world is turning towards AI for almost all sorts of decision making, both start-ups, as well as big tech giants, are offering lucrative salaries to in-demand Machine Learning jobs such as ML Engineers, Data scientist, etc.
As far as pay goes for Data Scientist job role, across all experience level and skill set, the median salary of a Data Scientist with Machine Learning Skills in India is around 9 lacs and whereas in the US it is around $92,000.
Below graphs from Payscale.com are depicting this:
On the other hand, if we talk about Machine Learning engineer job role, the median salary of Machine Learning engineer in India, across all experience levels and skill set is around 7 lacs, whereas in the US it is around $1,12,000.
The future of Machine Learning looks promising as the skilled talent pool for Machine Learning engineers is not yet enough to meet the growing demand for trained professionals. A report from the leading online job portal ‘Indeed’ says, since the beginning of the year 2018, employer demand for AI & ML skills has been consistent twice the supply of such skilled professionals.
Moreover, research from MarketsandMarkets depicts, by 2022, the growth in machine learning market size will be USD 8.81 Billion.
So, as you can see there are lots of opportunities lies in this field, this is the right time to upskill in Machine Learning. Prepare yourself by getting certified and working on real-life capstone projects to take advantage of Machine Learning career opportunities that come your way.
Now, with this, we come to the end of this Machine Learning Career and Future Scope article. Hope this article was insightful!
Edureka has a specially curated Machine Learning Engineer Master Program that will make you proficient in techniques like Supervised Learning, Unsupervised Learning, and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.
Got a question for us? Please mention it in the comments section of the “Machine Learning Career and Future Scope” article and we will get back to you.