Exactly how I Built a Data Scientific Research Portfolio That Got Recruiters Chasing Me


Proof beats guarantees each and every single time.

Photo by Deng Xiang on Unsplash

Most developers treat profiles like a checkbox. A GitHub repo with a few Jupyter note pads and they stop.

That used to be me as well. Up until I realized something: recruiters uncommitted concerning half-baked Titanic survival predictions. They care about whether you can address troubles that appear like their issues.

So rather than developing toy tasks, I flipped the manuscript. I constructed automations and information tools that resolved actual frustrations I had in my very own life. That shift alone turned my profile from “meh” to “must-see.” Right here’s how I did it.

Job 1: Automating Resume Tailoring

I was tired of rewording my resume for every single job. Very same skills, various phrasing. So, I automated it.

I wrote a manuscript that takes my Markdown return to and a work summary, then revises my resume with the appropriate keyword phrases utilizing OpenAI’s API.

  import openai 
openai.api _ trick="your_sk"
def tailor_resume(resume_md, job_desc):
punctual = f"""
Adjust this resume to match the work description:
Resume: Work
feedback: Resource
""
web link = openai.chat.completions.create(...

Resource link

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