u/rugveed

Hey everyone,

With all the AI-driven layoffs happening (Meta cutting 14,000 positions), I'm trying to be smart about what I learn next.

My current profile:

- Python, Pandas, NumPy, Scikit-learn, SQL, Streamlit, Git

- Projects: California House Price Prediction (deployed on Streamlit), Netflix EDA (Kaggle Bronze Medal)

- Day 50 of CampusX 100 Days of ML

- Starting a 3-month internship at an AI startup

What specific skills, tools, or areas should I prioritize RIGHT NOW to stay relevant and land a good Data Scientist or ML Engineer job/internship?

Any honest advice is appreciated. Thanks!

Hey everyone,

With all the AI-driven layoffs happening (Meta cutting 14,000 positions), I'm trying to be smart about what I learn next.

My current profile:

- Python, Pandas, NumPy, Scikit-learn, SQL, Streamlit, Git

- Projects: California House Price Prediction (deployed on Streamlit), Netflix EDA (Kaggle Bronze Medal)

- Day 50 of CampusX 100 Days of ML

- Starting a 3-month internship at an AI startup

What specific skills, tools, or areas should I prioritize RIGHT NOW to stay relevant and land a good Data Scientist or ML Engineer job/internship?

Any honest advice is appreciated. Thanks!

Hey everyone,

I’m planning a project and wanted some quick feedback:

Idea:

- Take a job description + resume

- Extract skills using NLP

- Compare them and give a match score + missing skills

Do you think this is too basic/overdone for a data science or ML resume?

How would you improve it to make it stand out more?

Appreciate any suggestions!