Key roles in AI

Artificial Intelligence (AI) caught the imagination of the business fraternity. Every side of the cube, I hear talks and opinions fly about AI. And, ask any developer, (s)he wants to enrol into AI/Machine learning course and find the next job. Remember coursera starter course.

Question I ponder here is – Is the same AI / Machine Learning course for every one? Or, is that the dev community wants to jump in and encash this bandwagon? All the while, my argument is that you cannot forget your past experience and jump into a whole new world of AI building models and predicting. There are multiple flavours coming in different roles. My recommendation is that, based on your past you should get into the one that suits you most!

  • AI / ML researcher – An academic role in universties. Expertise in AI / ML algorithms. Tasked to build algorithms cracking new problems and seeing new boundaries. Need research background.
  • AI / ML developer – Have insights into the existing algorithms and their endless parameters. Recommends an algorithm with the right set of parameters to solve the given problem and come up with a model. Works predominantly in R, Matlab, Python and ML toolkits. Need algorithm background.
  • Enterprise developer – Folks who make enterprise applications. Work with AI/ML developers and put the created model into production usage for masses. They would be interested in scoring side of AI toolkits. Need technology background.
  • Business analyst – Business role with the responsibility of leveraging AI capabilities in the business processes. Here, the innovation is how to take an AI capability and build a feature in the product (process) optimising it. Need BA/PO/ Domain specialist background.
  • Data scientist – Mine the given dataset, apply all sort of data mining, statistical, AI algorithms and come up business inference. Need statistical background.
Key roles in AI