5 Scientific Working Tips For Data Scientists

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Scientific working is a must for every data scientist. Unfortunately a lot of people don’t know how to do that.

This post is giving you five simple tips for scientific working you can start using today.

Follow them and get recognised and respected as a professional in any profession.

If you are writing a paper or doing a thesis you need to read this!

Honesty

The data is the data. The data doesn’t lie, people do and you are better than that.

Be honest.

I know everybody has his own agenda, but don’t let it influence your work.

Don’t twist the results to fit your agenda.

If you are writing a thesis and the outcome is not what you expected then be honest. Analyse the situation and find out why the results are like that.

You are working on a business intelligence task to to boost sales. You have a theory but the data does not support your theory.

No problem! Be honest, publish your findings and try to find out why it did not work.

Objectivity

Don’t let your feelings influence your work. Feelings have no place in science. Especially for interpreting results or writing a piece of scientific paper.

Stick to the facts and let the reader make up his mind.

If you are working in a team and you have a disagreement stick to the facts and don’t get personal.

Validity

Make sure that your conclusions are valid. Check and recheck the results.

You don’t want to tell management that you can boost sales 10% by giving out free teddy bears.

It is ok to make mistakes. But If you constantly slip up publish invalid results.

People will question your honesty, reliability and your competence. You will look like a fool.

One way is to try looking from different angles when re-checking your results. You could also ask a college to review your thought process and the data.

Review-ability

Your work needs to be reviewable. Review-ability builds trust.

People in the scientific community hate only getting the results. They are suspicious and want to know how you got to your conclusions.

Always document how you got to the conclusion.

Document your thought process and your methods. Try to include or link to source material or source data as often as possible.

Give people a chance to come to the same conclusions on their own way.

Conclusion

Honesty and objectivity will show people that you are a good source of information. That you don’t twist the data. That your results are not tainted by your feelings or your subjective opinions.

Incorporating reliability and validity will make sure that your works is good. That it is free of fault.

Review-ability makes people trust your work. Even if your conclusions sometimes sound crazy at first 😉

Sticking to those tips is going to help you establish you as a reliable source of good information. They will catapult you a big leap forward to being a professional data scientist.

Do you know some more tips for scientific working you learned the hard way? Write me a comment and start the conversation 🙂

Wait, there’s more!

There are three more topics for scientific working you need to know. I already published them. Check it out: 3 More Scientific Working Tips For Data Scientist

 

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