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3 battle-tested skills that every data scientist should have.
(and how to apply them to a job interview)🧵
#datascience #skills #rstats #python
(and how to apply them to a job interview)🧵
#datascience #skills #rstats #python
People don’t realize this but I was a data science consultant and corporate trainer...
That was long before I was a “teacher” and a “6-figure data science mentor”.
That’s where I learned these skills through battle-testing.
And my clients were my test subjects. 🧪🧑🔬
That was long before I was a “teacher” and a “6-figure data science mentor”.
That’s where I learned these skills through battle-testing.
And my clients were my test subjects. 🧪🧑🔬
1. Focus on results
Outcomes are what moves mountains. Not analysis.
Yes- data analysis is incredibly important.
But, what’s more important is what you and your company do with the analysis.
Outcomes are what moves mountains. Not analysis.
Yes- data analysis is incredibly important.
But, what’s more important is what you and your company do with the analysis.
💡Data Science Interview Tip:
Ask yourself how I can help the company with these findings?
Summarize it into a report or web app.
And put THAT in your portfolio.
Ask yourself how I can help the company with these findings?
Summarize it into a report or web app.
And put THAT in your portfolio.
2: Build Relationships
Companies are run by people. And every person has needs.
If you can lend a helping hand, then go for it.
Companies are run by people. And every person has needs.
If you can lend a helping hand, then go for it.
💡Data Science Interview Tip:
Pick 3 focused target positions.
And focus on how you can help them accomplish their goals with your skills.
Give them a short slide deck during your interview.
Pick 3 focused target positions.
And focus on how you can help them accomplish their goals with your skills.
Give them a short slide deck during your interview.
3. Operationalize
It’s not sufficient to make analyses and reports.
In fact, if that’s all you can do, then I wouldn’t hire you.
You need to be able to operationalize.
This means taking your analysis and making something that the business can use.
It’s not sufficient to make analyses and reports.
In fact, if that’s all you can do, then I wouldn’t hire you.
You need to be able to operationalize.
This means taking your analysis and making something that the business can use.
💡Data Science Interview Tip:
Make web applications your portfolio.
Don’t show code.
Show web apps that do the thing the company needs based on your analysis.
That’s your pitch. Your value add.
Make web applications your portfolio.
Don’t show code.
Show web apps that do the thing the company needs based on your analysis.
That’s your pitch. Your value add.
If you want a full guide on what you are up against...
I wrote a 155 page e-book that explains the 7 chapters on what I and many others have done to succeed in data science.
Table of Contents:
I wrote a 155 page e-book that explains the 7 chapters on what I and many others have done to succeed in data science.
Table of Contents:
- Introduction (The Way Of The Business Scientist)
- Chapter 1: The 14 Data Science Skills
- Chapter 2: The Business Science Problem Framework
- Chapter 3: The Career Path for a Data Scientist
- Chapter 1: The 14 Data Science Skills
- Chapter 2: The Business Science Problem Framework
- Chapter 3: The Career Path for a Data Scientist
- Chapter 4: How To Become A Financial Data Scientist (Case Study)
- Chapter 5: Why I picked R over Python for Data Science
- Chapter 6: Anatomy of a Data Science Team
- Chapter 7: The Data Science Workflow Framework
- Chapter 5: Why I picked R over Python for Data Science
- Chapter 6: Anatomy of a Data Science Team
- Chapter 7: The Data Science Workflow Framework
What's your next step?
👉Pick up your copy of my E-Book here: learn.business-science.io/if-i-had-to-le…
👉Pick up your copy of my E-Book here: learn.business-science.io/if-i-had-to-le…
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