[Course Link](https://ace-the-data-science-interview.teachable.com/courses) Nick Singh (co-author of [[Ace the Data Science Interview]]) presents a short course on the data science job hunt in four parts. ## Resume The sole purpose of a resume is to land an interview. You've got 10 seconds to impress the recruiter. Understand the first screen is a non-technical recruiter that needs to compare your resume to a long list of requirements provided by a hiring manager. Finally, keep it relevant and don't include anything that makes you look bad. You can put the resume sections in any order. Skip the summary. Bold what you want to emphasize. Add links to your projects. Put in metrics, any metrics, to make it look more quantitative. Focus on impact when you can. Integrate the skills in the bullets, but include a skills section towards the end for ATS. Drop ANYTHING that doesn't get you to the first interview. ## Portfolio Project Nick emphasizes building a single kick-ass portfolio project as opposed to multiple small ones. The best project is deployed with real users using industry best practices, etc. You can speak to the project from different perspectives for different job opportunities. Your project sucks if - it is a repeat of a common problem or dataset, even a Kaggle competition (assuming you didn't place highly). - it doesn't visualize well. You can't easily communicate what it is. - it isn't DONE (deployed, GitHub README, Medium article, compelling visual). - it lacks impact. Articulate the who cares and quantify it numerically. ## Cold Emails Use cold emails to reach out directly to hiring managers. Nick promotes pitching yourself "I saw this role and I'd be a perfect fit because...". Link to your portfolio project as proof. Recruiters are doing it, so you should do it right back. Use these 6 rules 1. Keep it short (50-125 words which is the best length for sales emails according to Hubspot). 2. Have a compelling subject line 3. Provide proof of accomplishments (add an image to the body of the email) 4. Relate personally 5. Have a specific ask (not a generic question you could have researched online). Maybe ask for a referral or to start interviewing. If you are asking for an informational interview, include two specific, intelligent questions in the email. 6. Establish a timeline and urgency. Follow up 3 times by continuing the conversation. Nick provides templates and examples on his [site](https://ace-the-data-science-interview.teachable.com/courses/1683053/lectures/41138358) (login required). ## Behavioral Interviews