Extract. Transform. Read.

Hi there, past, present or future data professional! Zach from Pipeline here; I hope you’ve found the data science project ideation guide useful.

Since that guide or the story it’s based on may have been your introduction to my humble publication, I wanted to share 3 resources, curated from 250+ articles that I intend to serve as actionable guides for breaking into or succeeding in the data science field from the perspective of someone who started with no computer science background.

Before I became a senior data engineer, I worked as a tutor and resume writer serving everyone from students to c-suite professionals. One of the rare long-reads on Pipeline, the guide below, 3+ Years of Data Science Job Seeking Advice In 10 Minutes, (split into multiple parts) combines my real experiences interviewing for 15+ jobs in the early 2020s with my unique insight as someone trained to prepare candidates for resume screenings, navigating network dynamics and crushing interviews.

One of the areas I cover, that not enough career advisors discuss, is how to precisely target roles to increase your chances of passing a resume screening and landing a coveted interview.

My starting tips:

• Avoid the scattershot method of applying to x companies a day; this will lead to burnout
• Make a list of 3–4 industries you have existing experience in or have a vested interest in learning about
• Make a separate list of 20-ish companies within that industry you want to apply to

The first part of the guide discusses the current data science job landscape, how to choose an industry/company, professional branding and developing a proof of concept project. Part II will be published next week.
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3+ Years Of Data Science Job Seeking Advice In 10 Minutes (Part I) Actionable data science job searching, application and portfolio strategies to compete in a tight data science job market. ​ Read more

I Got $75 For This Dashboard But Not A Job Takeaways from a controversial data science interview practice: The take-home assignment. ​ Read more

Not Getting Data Science Interviews? You Have A Visibility Problem Data science job applicants are facing more competition than ever; how to create and publicize compelling work to stand out — the right way. ​ Read more

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Thanks for ingesting,

Zach Quinn, Pipeline: Your Data Engineering Resource