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I recently used software for automatically running the modelling tasks I used to do manually. All I need to do now is just prepare the dataset for its use. I don’t even need to bother with the model tuning or scratching some middle steps or even adjusting the missing data there as the robot can return a ready-to-use output.

How can I keep myself valuable to deliver in my work and what skills should I develop to best suit myself for the future?

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    Learn the mathematical algorithms behind the model..that is where the real power of analytics is. Not coding or automating
    – PagMax
    Apr 20, 2017 at 2:28
  • Yes ,strongly agree @PagMax. I am spending time to go through the every algorithmic details and could you please say more detail about how this work can benefit me? Customize the algorithms?
    – LUSAQX
    Apr 20, 2017 at 2:30
  • Don't be so rash to give someone a down voting and leave more chances for them to improve. A down vote would take him one step ahead to be forbidden on asking questions.
    – LUSAQX
    Apr 20, 2017 at 5:06
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    most likely it is down voted because it may be considered as off-topic (what to do/learn). Usually good questions here are ones which involves other people in your team (related to obtaining, maintaining, leading or quitting your job).
    – PagMax
    Apr 20, 2017 at 6:27
  • Indeed, @PagMax is correct. You may want to read up on the close reason here
    – Draken
    Apr 20, 2017 at 7:02

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Learn about the company's goals and business model. Learn some of the theories and techniques used in the modeling, and try to find areas of improvement. Connect the modeling data and outcome to the business and see if there is more data that could be useful, maybe another output format or type of conclusion? Try to understand the modeling as deeply as you can. Very general advice, of course, without knowing your exact application.

Even if a lot of things can be automated it often takes a human mind to make sense of the outcome and make sure that the right things are automated. For example, some machine learning algorithms that take a lot of tweaking to get right and a lot of analysis to make sense of.

Math and automation are only tools to arrive at some business value, and it takes humans to connect the dots and turn conclusions into something useful most of the time. Try to thoroughly understand the tools and the process as well as how to automate it. If you succeed, I bet you would be very useful.

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