You will find here an unusual perspective and opinions about data science. These articles may resonate well with senior data scientists and decision makers who manage the data science budget in their companies, but not so well with junior data scientists (assuming it is possible to be both junior and data scientist.) Professionals in fields such as operations research, physics, engineering, FinTech, econometrics, biostatistics might find this content refreshing, even if they don’t call themselves data scientists. Eventually, most of us, at some time, graduate to become a real data scientist, even if we started as a pure tech geek.

- Why You Should be a Data Science Generalist – and How to Become One
- Becoming a Billionaire Data Scientist vs Struggling to Get a $100k Job – What is the difference?
- Is a PhD helpful for a data science career?
- If data science is in demand, why is it so hard to get a job?
- Why do people with no experience want to become data scientists?
- Why is Becoming a Data Scientist so Difficult?
- Full Stack Data Scientist: The Elusive Unicorn and Data Hacker
- Statistical Significance and p-Values Take Another Blow
- Are data science or stats curricula in US too specialized?
- How do you identify an actual data scientist?
- Why Logistic Regression should be the last thing you learn when bec…
- 5 Myths About PhD Data Scientists
- 22 Differences Between Junior and Senior Data Scientists
- The First Things you Should Learn as a Data Scientist – Not what yo…
- Data Science and Machine Learning Without Mathematics
- Advanced Machine Learning with Basic Excel
- The Death of the Statistical Tests of Hypotheses
- Biased vs Unbiased: Debunking Statistical Myths
- First Doctorship in Data Science

**DSC Resources**

- Book and Resources for DSC Members
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
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