Do You Have Data Science Experience But Lack Technical Skills, You’ve worked with data before, but when you read job postings, they all seem to want things you’ve never used or even heard of?

You’ve manipulated, organized, and mined several large data sets. You’ve even interpreted that data for others to use.

Nonetheless, while you appear to have a lot of experience handling and using data, you appear to lack a lot of the specific technical skills that many job postings require for different packages/languages/programs you’ve never heard of.

Rather than trying to figure out the ‘it’ package or language, your time would be better spent learning what the jobs you want require.

To begin, all data science jobs will expect you to know the fundamentals of the methods used in data science, so

a) brush up on your applied statistics,

b) become intimately familiar with a data science programming language (R or Python are the most recommended), and

c) learn the fundamentals of machine learning and be able to point to a meaningful project you’ve completed using the fundamentals.

That is the starting point for becoming a data scientist.

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Regarding the 20 different packages/languages/programs you’ve barely heard of, rather than attempting to learn them all, conduct a survey of all job postings that interest you.

Then, look at the data set of job postings to see which packages/languages/programs are mentioned the most.

If you are serious about getting one of these jobs, pick the top two or three most frequently appearing packages/languages/programs that you are unfamiliar with and begin learning them.

You will be more focused in your preparation for a data science job if you do this. This allows you to spend more time on things that matter and less time on things that don’t.

An example of how you could use this in your job search

The following question was asked in a recent forum posting: “Should I learn F# instead of another language?

Is F# a data language that people should look into?”

If the original poster is interested in programming languages, they should learn F#.

However, if the original poster is looking for a data science job and asking the question through the lens of a job search, the answer should be – it depends on how many of the jobs you want to apply for require F# experience.

If none of the jobs require F# experience and instead require NLTK (Python’s Natural Language Toolkit library), the person’s time would be better spent working on a project that requires NLTK rather than F#.

Especially if the individual has never used NLTK before.

On the other hand, if the majority of the job postings the person is considering require or recommend the prior experience with F#, then any time spent learning and working on a project in F# would be extremely valuable.

Your time is valuable when it comes to job searching – You don’t have to learn everything – just what the jobs won’t require you to know.

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Next Step

Your next step is to look at three job postings that interest you and look for commonalities in the packages/languages/libraries between them.

Then, for those who show up, determine which you don’t know. Finally, choose one to investigate this week.

This way, you’ll learn something new, bringing you one step closer to landing the data science job of your dreams.