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From Next Week, I will start series of posts for steps to understand your business and gain business users trust.
Normally fresh graduate data scientists are treated like fresh graduate doctors, no one believe in their predictive models (diagnosis) without knowing features (symptoms) used for predictions, Use white box techniques (Regression, DT..) to make predictions in your first models
Business trust can be gain by involving them in all Data Science phases and update them about your analysis outcomes and some of final prediction rules, this can't be achieved if you depend only on black box techniques like #DeepLearning
Once you gain their trust, they will support you to get accurate data from whatever source, get required resources to run your model and approvals to automate your model in production then after that continuous feedback
Your biggest challenge in your Data Science career, is how to win business owners trust (ex, marketers, Sales team,..) not data quality not ML algorithm, those people will be responsible for approve pushing your model to product and give you feedback about model results
Having AI systems in your Organization like chat bot doesn't mean that you become data driven organization, it is just a matter of automating human work same like having finger punch machine for recording your employees attendance
Core part in your data tasks will be guided by your awareness about how to make statistical analysis and armed by your IT skills for data manipulation
Data science is not just running deep learning model and keep waiting for it to do everything, it is a chain of work that starts from business problem and ends by business solution and in between huge bulk of data tasks
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