Future Work: Machine Learning Specialist

We talk a lot about AI implementation in business these days, but often what we’re really talking about is machine learning. This is essentially the application of AI via a learning algorithm. Such a software program is built to use AI to identify patterns in data, and then make decisions based on them. The amount of data these algorithms can handle is huge, and overall a machine learning algorithm will provide faster and more accurate results than we could ever hope to as humans.Machine learning specialists, then, are responsible for developing and subsequently ‘training’ algorithms to interpret data and make appropriate predictions. As AI becomes a more commonplace and essential resource for businesses, machine learning specialists are going to be in ever-increasing demand. Read on to find out what skills, qualifications, and basic knowledge you’ll need to get started down this career path.

Machine Learning Specialist

 

Basics


Becoming a machine learning specialist will require a good understanding of programming languages as well as statistics. Getting familiar with some key concepts that you’ll be hearing a lot of will also be useful. Spend some time getting comfortable with the following terms:

Once you feel fairly confident in your understanding of these concepts, think about how they are currently being applied across businesses and science every day. Here are some examples to get you started:

 

Skills


There are a few disciplines that are vital to becoming a machine learning specialist or engineer, which we’ll look at below.

 

Computer Science and Software Design
The first, as you might have guessed, is a detailed understanding of computer science and programming fundamentals. This means you’ll need a good working knowledge of:

  • Data structures
  • Algorithms
  • Computer architecture
  • Programming

You’ll also need to be confident with designing and implementing software. Machine learning software is almost certain to be used as part of a wider software network, which means understanding how to integrate what you’ve designed into a larger picture will also be key. Knowing how to test your creations, as well as make them easy to use for colleagues, will also be extremely important.

 

Statistics and Data Analysis
Interpreting stats is another crucial skill set for any aspiring machine learning specialist, as data science plays a big part in such a role. That said, you won’t necessarily need to be an expert in statistical analysis. Having a workable knowledge of some of the following concepts will be important, however, especially on a theoretical level – the idea is that your algorithms will do the heavy lifting, but you need to be able to understand any limitations, advantages, or disadvantages that programming your software to utilise these statistical concepts will raise. Some statistical approaches worth knowing include:

  • Sampling: when you use statistical information from a small section of a population. An example could be a survey of 200 people chosen at random and asked about their political views.
  • Probability basics: Probabilistic models in the field of statistic are those that incorporate random variables into the overall statistical model. As opposed to a deterministic model, which focuses on only one possible outcome, a probabilistic model will attempt to give a probabilistic distribution as an outcome. Essentially any statistical model with a random or unpredictable element will incorporate probability.
  • Data distribution: This enables you to understand and examine data from a variety of different perspectives. It can tell you how often certain values occur, as well as the density of those values.

Learning some specialist data analysis software like R or python is important too, as these tend to be the most favoured languages for machine learning software and applications.

 

Artificial intelligence and machine learning visual concept on a circuit board

 

Qualifications


Any qualifications in the following fields will give you an immediate advantage, especially if they’re at degree level or higher in subject areas such as:

  • Data science
  • Mathematics
  • Statistics
  • Computer Science
  • Programming
  • Software Development

Additionally, there are more and more specific machine learning courses springing up both online and at universities, including everything from short courses to Master’s degrees.

 

Career Potential


Once you’ve got the skills and qualifications, and feel confident about getting out there, you’ll find a myriad of interesting opportunities as a machine learning specialist. Just because it’s a tech-based role, it doesn’t mean you’ll be limited to working in the tech sector alone. In fact, almost any business that deals with data interpretation in some form will be looking to hire skilled machine learning specialists. This means, if current trends continue as predicted, you could well have the luxury of choice when it comes to choosing where to work.

Salary wise, a machine learning engineer in the UK can currently expect to earn around £70k or more per year, with senior positions commanding an impressive salary of around 100k. If you’re currently on the search for machine learning roles, or related data science positions, make sure to register with us today to set up custom job alert emails.

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