Thread by @mdancho84

There are more than 10,685,000 people learning to work with data.

Yet most data science jobs now have over 1000+ applicants.

And only 5 actually make it to an interview.

Use these 4 skills to stand out (free to steal & use to advance your career).

#datascience #rstats

1. Time series analysis

Up to 90% of companies need better forecasting.

And less than 5% of data scientists are competent in time series analysis.

So becoming good at time series is a massive advantage.

Demonstrate an application of time series analysis in the interview, and set yourself apart from the crowd.

2. R for research and development

Research is the 1st part of the data science lifecycle.

And the fact is that 80% of companies aren’t able to learn from their data.

They simply don’t have the people that can quickly turn knowledge into actionable insights.

Learning R is a key advantage because it takes 50% or less time writing code than comparable python analysis.

This means 2X or more projects get through the research phase.

And you can put 2X more data products in your portfolio.

3. Business problem-solving

75% of data scientists struggle with business analysis.

They know algorithms, theory, math, and statistics.

But when faced with a business problem, they freeze up.

To stand out, demonstrate skill in business problem-solving.

It’s easier than you think.

Focus on their problems.

Tie a financial amount to the problem.

Show how to reduce cost or increase revenue.

Then show how you would use data to help.

4. Demonstrate you can get projects into Production

Up to 73% of companies report difficulty getting a solution built and deployed.

This is incredibly frustrating given that data science teams of 10 or more…

And a costly mistake: $1,000,000+ per year to run the team.

You can stand out by demonstrating apps in your portfolio.

Why?

Because Apps are what organizations need to scale decision-making.

How to learn apps?

There is no better way than #Shiny web apps.

They are easy to build.

They are easy to deploy.

And while the 10-person data science team is struggling to get anything into production (taking 15+ months on average for 1 project).

You’re able to build and deploy a shiny app in about 1 month.

That's a productivity increase of 15X and...

A cost decrease of 90%.

There you have it: 4 skills that will set you apart from the competition.

Now you’re probably wondering how the heck can I learn these skills (and not take 2 years or longer of struggle)?

I put together a free webinar that gives you the blueprint to becoming a 6-figure data scientist.

Seriously, it’s packed with free value:

1. 10 skills to learn on your blueprint

2. 3 common mistakes to avoid

3. And a full plan to succeed in becoming a data scientist

What’s the next step?

Just watch the webinar, take notes, and start learning from your very own blueprint to becoming a 6-figure data scientist.

It's that simple. 👇

learn.business-science.io/free-rtrack-ma…