How I resynchronized that got me $100k+ data science and ML rendering

Over 100 Data Science and Machine Learning resumes, both as a doctor in the field and a career coach

And to be honest, most of them suck.

It's actually not that hard to write a good resume, but most people can't seem to get the basics right.

A good resume is what gets your foot in the door for interviews, so nailing this part of the interview process is important.

So in this article, I want to walk you through my report that earned me $100k + more in all data science and machine learning, and give my valuable advice in all categories.

Resume (at a glance)

If you don't have time to read the whole article, this resume is in PDF format from Latex (using Overleaf) and Google Doc Version.

If you want to get this template and learn how to use it, then check the link below.

The reason I have two versions is that the PDF version generated by Latex looks great, but can be a problem with the application tracking system (ATS).

That's why I have a different version in Google DIC format, which is very friendly.

An ATS is essentially an automated process that helps filter out people who aren't a good fit for a role or job description. Like any program, it has errors and sometimes conflicts with parte formats, such as PDF versions produced by latex.

Almost all Fortune 500 companies (99%) use Ats for Recruiting, and 75% of startups fail to pass ATS and are never seen by a recruiter.

So, if I'm applying in a situation where there's no guarantee that a real person will see it, like instant linkedin Apply or job forms, I use the Google Doc format to be safe.

If I know a recruiter, hiring manager or other physical person will see my resume, then I give them a PDF version from Latex / Overleaf.

Now let's break down each category and my top tips!

The latex template is based on this template by timmy chan. You can check out the source code here on his github. The template and code are under the CROMONS CC 4.0 license.

General Principles

I'm going to outline the very basic principles that resumes should follow. I think you might be missing at least one of these points:

• There are absolutely no spelling mistakes, and the grammar is correct. This is a huge red flag for anyone revising.
• Keep it 1 page, unless you have 10+ years of experience.
• Font sizes that match all categories and avoid excessive use of – wake up and silicification.
• No fancy formatting, keep it simple.
• No graphics, images or icons.
• Avoid anything that could lead to bias, such as age, gender, nationality, etc.
• Use bullet points, not block text.
• For your Google Doc Version, use an easy-to-read font, such as Roman Times, Calibri, or Georgia.
• For your PDF version, I highly recommend using latex, because it produces a clean and beautiful resume.
• Finally, if you have time, tail an entire section on your resume on a related job description.

Tiger

This section should be easy to get right, and I'm still surprised people find this section wrong at all.

All you need:

• Your name.
• Job title or how you see yourself. This is optional.
• Contact information, such as phone number and email.
• Place, city and country.
• Relevant links like LinkedIn, GitHub, Medium, Kaggle etc one thing to make sure the links work! They contain useful information about you, so you want to make sure that whoever clicks on them actually goes where they want.

Summary statement

If your resume is clear about what you did and who you are, then this section is not necessary. You will repeat yourself and you can use up valuable space on your resume.

For example, I personally don't have a summary statement, and I haven't (as far as I know anyway!). However, it can be beneficial when you want to align with a specific company or role, or play ATS a little.

One important thing I will say, it is very easy to go wrong here using words like “passion”, “hard work” or “determined.”

Don't do that.

I can't tell you the number of resumes I've seen where someone says you're hardworking, motivated and passionate.

This is the basis for any company that wants to hire.

A good summary statement clearly states who you are and what you have done in a few sentences.

For example, if I could do this to myself, I would write.

Data Scientist / Machine Learning Engineer with 4+ years of experience covering time series forecasting, research / capitalization problems and applied machine learning. The domain expert lies in insurance, the provision of the provision of facilities from various companies that I have worked for.

No fluff, straight to the point.

Technical skills

This is a very short summary of all your skills, and I really shouldn't exceed 4-5 lines and that's too tight.

This is great on a resume because it will quickly help the employer know that you meet the job's technical requirements.

Now, usually, people will present many red flags at this stage without realizing it. They think they're adding the things recruiters and hiring managers want to see, but in reality it's the exact opposite.

Let's break down the most common mistakes:

• Don't write too many technicalities; This looks suspicious. I might be skeptical if you list something like “Python, SQL, C++, rust, assembly.” It seems like a bunch of buzzwords, and I would find it very uninteresting to sculpt it all to the right level.
• When it comes to coding skills, it's best to use language like “PROPELY” or “Familiar.” Avoid using star ratings to contradict “Python 4/5” or say “advanced.” This way, you set realistic expectations and ensure that your skills are well represented. My guess is that if you feel comfortable answering simple leetcode problems in that language, then you are good at it.
• Don't write every Python package you know. If you are applying for a data science position, I assume you are familiar with nunpy, pandas, and matplotlib; There is no need to state this clearly. Instead, write things like git, AWS, argo, bash and Datari, which are real skills that every candidate will have.

Experience / projects

The most important part here is to show exactly what you did in each company and what the result was, you always use mankind and Prices. Ideally, they would have a financial impact.

Don't try to be too humble; It really “flexes” the work you've done and the impact it's produced. Really show off your skills.

For example, notice in your resume how I discuss technical measures or models such as “Arimax” or “Xgboost” with the aim of better forecasting or predicting business development, and finally tying that to the business impact.

This shows my technical skills and that I think about the business impact of my projects.

When you think about it, companies only care about the financial benefit you bring. Whether you use a neural network or linear regression, it doesn't matter.

Profit is profit.

It may seem too good, but it's true, so if you can directly show how you know how to link technical topics like 80% of applicants.

This is the outline I recommend for following all the bullet points in the experience section:

• Say what you were analyzing, predicting or modeling.
• Mention the techniques, algorithms and calculation tools you have used.
• Mention the metrics you've developed.
• State the amount of business you have generated.

Another thing is to be clear about the specific technologies, packages and algorithms you used. It's better that way than using vague language, and it will also allow you to hit ATS better.

Some more, but the obvious ones are:

• Include only paid work experience, but research experience is fine.
• Start with your most recent job and work backwards chronologically.
• Differentiate between internships and full-time positions.
• Do not use random points; it is not necessary.

If you don't have experience, replace this with the project category and make synonyms for the technical and business aspects. Try to list projects that are closely related to the role you are applying for to show interest in that area.

Education

If you don't have relevant work experience, I recommend putting the education section before the work experience and the project section after that.

As I have 4+ years of experience, my education level is simple. I keep a bunch of science and machine learning jobs explaining the need for a master's degree in the stem topic.

If you have no experience, you can skip this education section and discuss any relevant work you have done at your level. However, I don't recommend that you remove all your modules as is, and to be honest, no one really reads or cares. A few extra things to take care of

• If your grade is impressive, write it down; Otherwise, leave blank.
• List any special things you have done, such as hackathons, projects etc.
• List any prizes and awards you received while at school.
• Leave off course certifications, unless it's something like “AWS Practitioner” or you have loads of space left.

Activities / Extracurricular

This is optional, and many people will say not to add this section.

I think, however, that showing a little personality in your resume is not a bad thing, but it is certainly not necessary, and this can be the first section to cut if you are short on space.

I use this part to show my YouTube channel and blog posts, as it adds to my resume, but this is a rare case.

So, if you have something similar that you want to say, this section is very good for that purpose.

Earlier, I discussed how if you don't have experience, you should replace this with the projects category.

But what projects should you do to get hired?

Well, here's a question I answered in one of my previous articles, which you can check out below: