How to find an entry level data science job starting from zero?
By: Przemek Chojecki
Tags: Data Scientist, Data Science, Education, Learning To Code, Machine Learning

How to find an entry level data science job starting from zero?

Is becoming a data scientist with no coding background possible?

Data Science is a great, intellectually challenging career. Primarily Data Scientists are tasked with:

cleaning and preparing data sets

analysing data sets looking for patterns

extracting actionable insights from data

They tend to work both with the management (communicate insights), the internal team (looking for more data) as well as external clients (understanding what accuracy is needed).

How to find an entry level data science job?

In recent years data science went from a niche domain to an essential component of any larger business. The need for data scientists grew and after some time also the number of data scientists.

We’re currently past the time of easy entry to the data science market. There literally hundreds of applications for junior data science positions. So if you’re motivated primarily by a good salary ($100,000+ in the US at more senior positions), then think again. You’ll be competing with passionate people willing to work a lot towards their goals.

However, if you love solving problems, if you’re not scared of intellectual challenges and have enough persistence, then don’t worry. It might take some time to become a junior data scientist but you will get there. Be patient and code your way to success.

In order to find an entry level data science job you will need:

good knowledge of Python — enough to import and manipulate .csv files, scrape the web and connect to various APIs.

— enough to import and manipulate .csv files, scrape the web and connect to various APIs. command of prediction, classification and clustering algorithms — basics of various regressions, KNN or k-means.

— basics of various regressions, KNN or k-means. Github portfolio — presentation of your past projects on Github to show what you were able to do.

— presentation of your past projects on Github to show what you were able to do. up to date LinkedIn profile — a good online presence with clear statement of your previous education and workplaces is also a must. Be transparent.

Then it’s time to do some research on jobs available in your region (or elsewhere, if you plan on working remotely) and start applying.

A good way to start is also working on Upwork or Fiverr. These two services connect freelancers with companies. You’ll be able to apply for particular projects, from simple Django app to complex machine learning problems related to actual business. It might also in hiring you full-time later on.

Finally, Upwork and Fiverr will also show you what kind of skills are looked after: what algorithms, what technology stack, what kind of projects. This knowledge is invaluable to navigate the data science market.

Data Science Job course

So you’ve decided that you want to become a data scientist but don’t know where to start?

Or you have finished one or two courses on Coursera, read a couple of books and don’t know where to go from there?

Or you’ve started applying for data science jobs, but you stress about doing something wrong?

Don’t worry.

If this is the case, then my Data Science Job course is for you.

I have prepared it with an idea to connect the (data science) dots. There are plenty of data science courses online which can teach you about algorithms and plenty of books with great material, however, there are not enough materials about the process of becoming a data scientist:

what courses to take,

what books to read,

what algorithms to learn,

how to look for a job,

how to prepare for an interview.

This is what the Data Science Job course is about. It’s about giving you the knowledge and confidence to find your first data science job.

It’s a live course, which means I regularly add new video and expand previous materials. Pay once, learn for life.

And on top of everything, we have a Facebook group for our students to exchange thoughts and struggles and help each other.