The industry is exploding with Machine Learning, starting from the application of smart algorithms in smartphones, e-mail and marketing campaigns, Machine Learning is everywhere. So, if you are looking for an in-demand career, ML can provide you with just the right opportunity. Set up yourself with the right skillsets, and you are always good to go.
Machine Learning Engineer
As the name suggests, the work of a Machine Learning Engineer is run various ML algorithms and experiments for a company to come up with valuable outputs. An ML Engineer needs to have a stronghold on high levels programming languages such as Java, Python, Pearl and Scala to make use of the most ML libraries. Certain skillsets such as Programming, Probability, Statistics, System Designing and Data Modelling are also required to become a Machine Learning Engineer. So, if you are someone who has a huge interest in ML and AI, this is the job you must be looking for.
Data Scientist
Believe it or not, Harvard Business recently published in their article that Data Scientists is the ‘Sexiest Job of the 21st Century.’ While this title might motivate a lot of booming individuals to become one, but there is a lot more flexibility to this job as compared to others. The work of a data scientist is to collect, analyse and interpret the huge amount of data with the help of Machine Learning and Predictive Modelling so that corporates can have an actionable insight. A Data Scientist aids the majority of the decision making in a company.
NLP Scientist
NLP stands for Natural Language Processing. As the name suggests, the entire reason behind NLP is to provide machines with the ability to understand human language so that we can break the linguistic barrier between the machines and humans. In the recent few years, NLP has truly evolved to make conversations with humans. The general work for the NLP Scientists is to work on speech recognition so that the machines can have a better understanding of the fluency, phonetics, syntax and more importantly the grammar associated with a particular language.
Business Intelligence Developer
Business Intelligence Developer is the next big thing that comes after the data scientist. With the use of Data Analytics and ML, BI Developers ca collect, analyse and interpret a large amount of data for a clearer insight into the consumer domain. It is with the help of BI developers that enterprises can make better business decisions. A BI Developer also needs to have a vast knowledge on some of the commonly used programming languages such as SQL, Python, Perl, Go, Scala etc. Power BI is a great tool that complements the work of a BI Developer.
Human-Centric Machine Learning Designer
The work is just as obvious as the title defines it. Human-centric Machine Learning is associated with applying ML algorithms to make choices easier for the consumer. A great example of such is from the video rental services like Netflix, which provides their viewers with customised choices for a smarter viewing experience. The Human-centric ML uses the information processing and pattern recognition mechanism, which allows them to learn from individual preferences.
Conclusion
This article has only focused on the majority of the job roles that are being offered for Machine Learning. There are several other job descriptions associated with Machine Learning which you can consider as your career path. Whatever you choose, you are bound to outshine your peers, since Machine Learning has got your back.