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Have you ever been in a situation where you spend a lot of your time and energy learning something, only to realize that the skills you have gained don’t match or live up to the requirements listed by the employer? If this happens to you, you’ll have to begin learning new technologies and skills to get to the interview, which is one of the most painful and tedious tasks in the job searching process. Unfortunately, many people go through this tiresome loop.
With the recent buzz around machine learning, many courses have come into existence offering a broad curriculum. This leaves job seekers confused about what they really need to learn to become machine learning engineers. So, today we will try to find a solution and put you one step ahead of your rival ML job seekers.
After our previous analysis of Data scientist job descriptions, we have received numerous requests from people asking about a similar analysis on machine learning. That is why we conducted this analysis in an identical manner – by leveraging job boards data.
We analyzed more than 500 recent machine learning engineer job postings, and this analysis was mainly focused on the USA.
Now, let’s set our expectations straight from the start. We will try to answer the most common questions every machine learning engineer enthusiast needs to know.
You can find the answers to all these questions in the video below or just scroll down to keep reading.
What is the most sought-after educational background? Well, this is one of the most common questions among job seekers because there is a lot of confusion in the job market. Nobody has a clear idea about the ideal educational background required to become a machine learning engineer. So, let’s see what the data tells us.
According to our research:
In addition, what is worth noting is that most of the job ads are flexible in terms of the type of degree. For example, very often we can see Bachelor’s as required and Master’s/Ph.D. as preferred.
In terms of degree specialization, it appears that Computer Science, with Statistics and Mathematics as the not-so-close second and third place are the three specializations employers are looking for the most. Electrical engineering and physics are the other two most frequently desired degrees.
Now that we’ve covered the degrees and fields of study required to become a machine learning engineer, let’s take a look at the companies that are actively recruiting. Who are they?
Here are the top 10 companies in our dataset with the most machine learning engineer job openings.
As you can see, Apple undisputedly tops the list with almost 60 available offers, followed by Twitter, Amazon, Facebook, Snapchat, and TikTok. These are some of the most exciting firms in tech field, which extensively rely on machine learning to run their platforms. So, no surprise here.
Regarding company size, it is obvious that the majority of the offers are coming from big firms with more than 10,000 employees.
However, there is a considerable number of postings by both mid-range firms (1000 to 10,000 employees) and smaller firms (with less than 500 employees).
Next in our study, we analyzed the industries with the highest concentration of machine learning engineer job offers.
Unsurprisingly, there are more postings in the IT and Retail/Wholesale industries at the moment. But these are far from your only options, as there’s a substantial number of offers in the Consulting, Education, and Finance industries, as well.
This gives us an idea about the companies hiring ML engineers. However, to be thorough, we need to take a look at geography, too. Here, we split the data based on the state and city where the offers came from.
In terms of states, the majority of machine learning offers (almost 50% of our data) are from the state of California.
After California, there seem to be a good number of opportunities in New York, Washington, and Massachusetts.
If we consider cities where these jobs were available, we can see three important findings:
Now that we’ve outlined the landscape for ML engineer job postings, it’s time to pay attention to one of the crucial factors to land this lucrative job – working experience.
According to the data, there are generally more offers for people with at least 2 years of relevant experience. For comparison, there seem to be more offers in the range of 1–5 years of experience and fewer opportunities for 5+ years-of-experience candidates and freshers at the moment. And that’s certainly good news for those of you who considered many years on the job as a hard prerequisite for this position. But let’s elaborate on the experience factor a bit more – this time in relation to degrees.
On average, the experience required with a Bachelor’s degree is 4 years, while for Master’s degree, it’s roughly one year less – 3 years.
On the other hand, if you hold a Ph.D., then you’ll need 2 years of experience. However, there is a little catch here, as most of the recruiters haven’t mentioned the required experience for Ph.D. holders specifically. They mentioned it in a generalized way like: Required 2+ years of experience with education in MS or Ph.D. So, overall, if you have a Bachelor’s degree, you stand a pretty good chance with ML employers, provided that you have worked for a few years and you have acquired some valuable experience.
Moving forward, it’s time to dissect the most practical aspect of landing a machine learning engineer job – the required skillset.
In terms of general skills for the machine learning engineer position, we discovered the following:
To be a machine learning engineer, obviously, machine learning is the primary skill required. In addition, most of the jobs have mentioned deep learning and its fields like Natural Language Processing (NLP) and computer vision as a requirement. But that’s not all! There have been plenty of mentions of data analytics, statistical modeling and data visualization, as well. Big Data, version control tools like Git and deployment tools like Docker have been requested in quite a few descriptions, too.
How about we dive deep into each type of skills required?
Starting with programming languages.
No surprise here – Python is leading the chart with a significant number. What’s worth noting is that C++ and Java are mentioned more frequently than R, and SQL is mentioned in quite a few jobs, as well.
Continuing with the most sought-after skills, we can’t skip deep learning frameworks:
Tensorflow is leading our chart with Pytorch as a close second. Then the top two are followed by Caffe and Keras. Tensorflow and Pytorch definitely look like the two most popular frameworks at the moment.
Being able to work with different packages that are suitable for the task at hand is an essential skill for a machine learning engineer. So, let’s examine the most frequently requested Python machine learning packages.
Scikit-learn, where most of the machine learning algorithms and all other important functions are available, is listed as the top package, followed by pandas – one of the important libraries for all data manipulation activities. In third place, we have NumPy and SciPy where, basically, all the important math functions reside.
Spark tops the list with a significant lead over Hadoop, while Hive and Kafka have been mentioned in fewer job postings.
In terms of cloud technologies, AWS is the most in-demand cloud technology at the moment with Google’s GCP and Microsoft’s Azure following in its footprints.
Are data visualization skills important for an ML Engineer?
According to the data – not really. In fact, there are very few mentions of Data visualization tools for machine learning jobs. Tableau was mentioned just 15 times, whereas Power BI only 2 times, which makes it clear that the default packages in Python should suffice for aspiring ML engineers when it comes to data visualization.
Last on the list of ML Engineer job requirements come communication skills.
This one is slightly different than all the other skills we have seen until now. Apart from regular technical skills, communication skills appear to be equally important. Let’s see how many jobs have mentioned strong communication skills explicitly.
220 jobs have a mention of communication skills as a definite requirement for the desired candidate.
Now, you’ve got a good idea about the skills and education required to land a machine learning engineer job. One last piece of advice from our side: knowing technology is one thing and applying it is a whole different thing. So, to be successful in the ML field, learn the most mentioned important skills first. Then try to solve a real-world problem by combining all your skills to get a more real-life-like experience.
Remember machine learning is a very dynamic field, so be ready to upgrade yourself every day.
That said, if you want to sharpen your predictive modeling skills, check out our Machine Learning in Python course.
The post How to Become a Machine Learning Engineer? appeared first on 365 Data Science.
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Digital platforms have become a common norm. With the world going digital and people opting for digital platforms, a lot of data lies astray. This makes the virtual world prone to cyber threats and cyber-attacks. It is because of this reason that companies are now looking for ethical hacking certified individuals. Many working professionals also opt for ethical hacking training. Cyber security is a primary concern for many companies. They are now looking for individuals who can help in the assessment of the present network, find out the area of vulnerabilities, and at the same time, they can find the right solution for the same.
Do you remember the Capital One hack? Well, it was one of the biggest cyber attacks in 2019. It impacted almost 106 million users; the next whooping number comes from Ecuador’s data breach. It exposed the personal details of more than 20 million citizens. Even the Government of Texas faced the brunt of ransomware attacks. The series of attacks cost the loss of $12.
These are just a few of the prominent attacks which clearly raise the dire need for an improvised system, which is free from attack. One of the most in-demand positions is that of ethical hackers. These are cyber security professionals who have expertise in cybersecurity, and they can easily check if the system has any loopholes; they also check the network for vulnerabilities, and if any, these ethical hacking experts check the system and rectify the errors.
In the digital age, data is the king and is driving most of the industries; hence there is a need for a system that is free from cyber threats. A cyber security expert will help in creating a system that can act as a defense system.
In simple words, ethical hacking is a process of creating a system that is free from errors and also resists cyber-attacks. The primary objective of ethical hacking is to improve the security system of any organization. 2019 was flooded with cyber threats and attacks, clearly indicating that the conventional system that we are using is prone to cyber threats and attacks. Thus showing a need for an ethical hacking expert who can leverage this technology.
It is not just about the demand for cyber security professionals, but at the same time, a cyber security expert can earn an average salary of $91,000.
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If you too are looking to make a career in cyber security, then the following steps are going to guide you in the same:
These are a few of the things that hackers need to do. They need to learn about the system, assess the vulnerabilities, and find the right solution for the same.
If you have become ethical hacking experts, then you will be required to do the following:
Your next move should be enrollment for a good cyber security certification program. You can choose the Global Tech Council. This is an online forum offering the best online certificate program. As a part of this program, you will get to know about all the details of cyber security and learn its application part. If you wish to become a cyber security expert, and are looking for the best cyber security certification program, then you must connect with the Global Tech Council today.
How To Learn Ethical Hacking: 3-Step Guide was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.
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