Resume Review
Hello guys, I am applying for Data Scientist/ Data Engineer/ Machine Learning Engineer roles. All, I am getting are rejects. I would be very grateful if someone can provide me some insights on my resume. For context - Did a masters in CS, have about 4 YOE as a data scientist. EDIT - I got furloughed from my current job, so I am looking for new one. #tech #resume #faang #maang #google #microsoft #meta #apple #amazon #lyft #walmart #airbnb #netflix #oracle #nvidia #ibm #adobe
“Projects” section seems sort of irrelevant and makes you seem more junior. Are these projects from your school work? For the research paper, include a link and the full title of the paper, makes you sound more impressive. Move skills to top and education to bottom. Also PySpark is not a language.
Yes, projects are from school work. I worked on transformer models during my school, so added them just in case. I will include the link to paper and correct the pyspark thingy. Rest all seems fine ?
Typically, the first person reviewing a resume, often a recruiter, might lack technical expertise. Complicated bullet points might disinterest them. I personally found myself zoning out while reading your resume, even though I didn't have an overwhelming number of other resumes to review. I would recommend revising the bullet points to be more easily understood by anyone, regardless of technical background. This way, your message will come across clearly and captivate the reader's interest.
Okay. thanks for your reply. I will try to revise them, including less technical details.
I am currently interviewing to recruit BIEs into my team. It’s a non technical team that needs some BIEs to do our everyday statistical analysis. So I can give you feedback based on my experience so far. As a non technical stakeholder, your resume doesn’t really tell me what value you add. I don’t care about how complex the project was that you worked on. I want to see the quantified impact of your work on the business. Try to represent outcome based on cost, revenue, timeline, etc. If your complicated projects aren’t driving those numbers, it doesn’t really say much about the impact. I interviewed a candidate yesterday. His answers to basic STAR questions were very technical and jargon heavy. I’m sure those jargon’s are relevant to the data domain but I don’t understand them and hence cannot evaluate them. So I didn’t really find much value in his first answer. I asked him to to “dumb it down” for me during his second answer. His second answer was way clearer and easier to comprehend. That is basically what caught my attention. He’s been moved to the next round. A recruiter might see it the same way. Your work appears to be super rich and relevant to the data science domain. But try to make the representations more business friendly.
Okay. I will try to quantify some of the work I have done. Thank you so much for your feedback.
Are you on visa ?
Yes, F1 to be specific
Why are you leaving your first USA job after 6 months
I got furloughed from my current job.