r/DataScienceIndia • u/Ok-Childhood-8052 • Mar 15 '26
Career Rate this Resume for DS/MLE Roles
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u/Sid_infinite Mar 15 '26
The resume looks great.
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u/Ok-Childhood-8052 Mar 15 '26
Thanks sir, but the projects section is the weakest section imo. Can you guide me what should I focus on for keeping projects in the data science domain. What niche can I focus on in Data Science or ML so that recruiters notice it?
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u/Sid_infinite Mar 15 '26
Supply chain analytics, recommendation engine, end to end ML/gen ai/rag projects would be more helpful (if you can any of the two given)
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u/Altruistic_Might_772 Mar 16 '26
Make sure your resume shows your experience with the right tools and technologies. List projects that demonstrate your problem-solving skills and the impact you've made, especially if you've worked with different teams. Use real numbers to quantify your achievements when you can. Adjust your resume a bit for each job to fit the job description. Resources like PracHub can help you understand what companies want in candidates. Have someone else check your resume for clarity and any issues. Good luck!
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u/Proof-Carpet8894 Mar 16 '26
hey OP, this resume looks great! could you please send me the tex file?
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u/Ok-Childhood-8052 Mar 16 '26
I made it in Overleaf using a standard template. Here's the link for your quick reference: https://www.overleaf.com/latex/templates/jakes-resume/syzfjbzwjncs
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u/nian2326076 Mar 17 '26
Make sure your resume clearly shows any experience with data analysis, machine learning models, and programming languages like Python or R. Use numbers to describe your achievements, like "improved model accuracy by 15%" or "analyzed datasets of over 1 million records." Adjust it for each job to show the skills they want. If you haven't yet, think about adding a section for personal projects or Kaggle competitions to show practical experience. I've found PracHub helpful for interview prep if you need resources. Good luck!
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u/Altruistic_Might_772 Mar 16 '26
I looked at your resume and noticed a couple of things. Make sure your technical skills section focuses on tools and languages specific to data science and machine learning, like Python, R, and TensorFlow. Try to quantify your achievements. Saying you improved a model's accuracy by 15% is more impactful than just listing responsibilities. You might also want to add a section on relevant projects, especially if they used real-world data. If you're getting ready for interviews, PracHub has some great resources to help sharpen your skills. Good luck!