650%.

That's how much the demand for data scientists has grown since 2012. In the US alone, there are roughly 35,000 people skilled in data science, with hundreds of companies lining up to hire them.

According to LinkedIn's 2017 U.S. Emerging Jobs Report, data scientist has been ranked second in its Top 20 List of Emerging Jobs, with a 6.5x jump in growth in the 2012-2017 period, right behind Machine Learning Engineer.

With such astronomical growth in the demand for this role, you'd think bagging a data scientist role would be a piece of cake.

Well, think harder.

How do you think you'd go about getting a data science job? You think you just need to get a certification and you're done?

Well, there's one tiny step missing in that trajectory. The data science resume.

That singular piece of document which will make or break your chances of getting shortlisted. You might be able to process hundreds of TBs of data for gleaning valuable insights, but if your machine learning resume lacks the punch, it'll all be for nothing.

Fret not. The experts at Hiration have made hundreds of data science resumes, and we've helped professionals land those high-paying gigs you read about in Amazon and Google. So trust us when we say that we know what we're talking about.

Our 2019 Guide to Data Scientist Resume will:

  • Show you how to prepare a machine learning resume that will get you shortlisted
  • Nuances of a data science resumes
  • Do's and Don'ts of a data science resume
  • Sections of a machine learning resume
  • Data Scientist Resume Samples, Data Scientist Resume Examples & Ready-to-use Resume Templates to get you started!

Our in-house resume experts have created a state-of-the-art online resume builder containing ready-to-use content templates and ATS-friendly resume designs to give you an edge over others!

Don't believe us? Try it for yourself!

Our 2019 Guide to Data Scientist Resumes will broadly talk about the following:

Look at the below-given data science resume sample to see how a finished data scientist resume looks like:

LEONARD_HOFSTADTER_Data_Scientist_New-1--1

Why Do You Need a Data Scientist Resume?

Now that you broadly understand the demand for data scientists, and how it's only set to go up in the next 5-10 years, let's talk about data science resumes.

You'd think that with such an incredible demand, all you need to do is just walk in and you'll be greeted with open arms, right?

Well.

Here's the thing. Data is the new currency. Most companies realized it before it became a buzzword. And data scientists (along with ML/AI professionals) are going to rule the job market in the foreseeable future.

And you know that? Data scientists know it all too well.

It doesn't matter if you're a startup selling dog footwear or a Fortune 500 company. Companies know that there's no growth if there's no data. They know that without data, there's only so much they can do. But with data...well that changes things.

Online courses decided to join the bandwagon when data scientists became the new rockstars. Suddenly, the world was flooded with online courses that promised the stuff of dreams. You know $200k salary, benefits, remote work - the whole extravaganza. So who in their right minds wouldn't want a piece of that?

Before anyone could figure out what was happening, suddenly everyone was a data scientist. All you had to do was sit at home and complete the course in a few months...and bam! You're a data science professional.

While the demand is rising as we speak, the market has been flooded with data science professionals, with only a few certifications in their name. These online courses sure add a lot of value, but the recruiters now have a new problem: how to sift through all the applicants and filter out the best ones?

That's where your machine learning resume comes in. A data scientist resume is an opportunity for the applicant to stand out from the crowd, to convince the recruiter that they offer more to the table than just their certifications.

A data science resume will give the recruiter an idea around your qualifications - whether you only have a few projects under your belt or whether you know your way around data.

Now that we know the importance of a machine learning resume, let's waste no further time and dive into the nitty-gritty of a resume for data science. Additionally, you'll find data scientist resume sample in the end to provide further clarity on how a final data scientist resume should look like.

Data Scientist Resume - Best Resume Format for a Data Scientist Resume

When it comes to the format for a data science resume, what all options do you have?

Broadly speaking, you have three. Let's talk about the pros and cons of each.

Reverse Chronological Resume Format

The most conventional resume format in the market, and a darling of the recruiters, the reverse chronological resume format is the best bet for a data scientist resume.

As the name suggests, this resume format entails listing out all your experiences and qualifications in reverse chronological order. This means listing out your most recent qualification/experience first, followed by the previous ones, till you reach the beginning of your trajectory.

Sections in a Reverse Chronological Resume Format

A data scientist resume in a reverse chronological resume format contains the following sections:

  1. Header
  2. Personal Details
  3. Title
  4. Professional Summary
  5. Technical Skills
  6. Key Skills
  7. Professional Experience
  8. Education
  9. Certification, Conferences, and Publications
  10. Additional Information

It's always better to keep the target profile in mind when you're sending across your data scientist resume.

Pros and Cons of a Reverse Chronological Resume Format

While the reverse chronological resume format is the most preferred resume format, it's important to understand if it'd be suitable for you as an applicant or not.

Below are the benefits of going for a reverse chronological resume format.

  • ATS Optimized
    The reverse chronological resume format is ATS-friendly and is the industry standard when it comes to resumes. Going for this format will guarantee that your resume is effectively parsed by an ATS.

  • Preferred by Recruiters
    Since the ATS is able to effectively parse resumes in the reverse chronological format, it is preferred by recruiters as well. This format allows the hiring managers to quickly scan the resume for information which they think is most relevant, thus saving a lot of valuable time.

  • Ease of Preparation
    If you are a data scientist making your resume for the first time, or if resume writing is not your most preferred way of spending time (trust us, we understand!), you can simply opt for a reverse chronological resume format.
    All you need to do is create a timeline of your professional trajectory and expand each item in your resume.

  • Prioritizing your most recent work experience
    It'd be very rare if you land a data scientist gig right out of college. Usually, a data scientist requires a certain level of experience. You don't necessarily need an IT background for pursuing data science as a career.

But you don't want the recruiter to go through your earlier profiles. What do you do then?

Enter the reverse chronological resume format. This format allows you to put more emphasis on your most recent work profile. Consequently, your earlier roles (which are not related to your target profile) will be sidelined in place of your most recent professional profiles.

These were the benefits of going for a reverse chronological resume format. But in what all cases is it not applicable? Let's find out.

  • Gaps in your career
    If there are gaps in the professional trajectory, this resume format will make it evident to the recruiter. Since the dates are mentioned for every qualification and experience, not only will the recruiter notice that, but the ATS might also disqualify you (in case you lack the required work experience).

  • Frequent job switches
    If there are a lot of companies across a limited time frame, this might send a signal that you are an unstable employee who might not stick around for long.

Functional Resume Format

At the other end of the spectrum lies the functional resume format. Here, only the professional headers are mentioned, without diving into the details of each work profile.

Instead, a separate section is created along the lines of Summary of Skills, wherein the relevant points are grouped under the appropriate skills.

To clarify, the experts at Hiration don't particularly recommend this resume format. That being said, this resume format is ideal for those who have a lot of gaps in their professional trajectory, or those who have a history of frequently switching jobs.

Following are the pros and cons of using the functional resume format:

PROS

  • Covers employment gaps
    Since this resume format focuses on skills over the actual professional trajectory, this format is suitable for those professionals who have a lot of gap in their career.

  • Addresses the issue of job switches
    The emphasis on skills allows the applicant to put the focus on skills, thus allowing the recruiter to gloss over the factor of frequently switching jobs.

CONS

  • Not ATS-friendly
    The functional resume format is not
  • Suspicious to recruiters
  • No focus on the trajectory

Combination (Hybrid) Resume Format

The combination resume format or the hybrid resume format is a combination of both reverse chronological resume and the functional resume.

The first half of the combination resume is written using the functional format. So, the first half of the combination resume focuses and highlights a persons skills and accomplishments.

The second of the combination resume is written in the reverse chronological order, which means, the professional history of a person is written in the reverse chronological order.

PROS

  • Provides the information in reverse chronological order
  • Highlights the skills

CONS

  • Consume more time
  • Might not comply with company-specified guidelines

Writing Your Data Scientist Resume

We've divided the data science resume into three stages to make the data scientist resume making the process simpler. These three stages are:

  1. Master Machine Learning Resume
  2. First Draft Data Scientist Resume and
  3. Final Data Science Resume
  • Master Data Scientist Resume: Making the master data science resume is the proprietary method used by experts at Hiration.

This makes the data scientist resume making process easier going forward. A master machine learning resume basically has all the information, and by that, we mean every single thing that you can think of adding in a data scientist resume.

It is of a lot of help even in the future, when you need to update your recent data science resume in case of a job change or career change.

A machine learning resume is supposed to be of 2 pages at max, but since a master data science resume contains every little detail about your career, so it can exceed to as many pages as it takes to put all that information in it.

Then later in the data scientist resume making process, you can pick up the most important and valuable information from the master data science resume to make your final machine learning resume.

But at the master data science resume stage, you don't have to decide what all information will go in the final data scientist resume and which will not.

The idea of a master machine learning resume is just to collect all the information at a single place.
For example, if you are responsible for the following duties, say:

  • Building and optimizing classifiers
  • Data mining
  • Enhancing data collection
  • Data processing
  • Conducting ad-hoc analysis
  • Creating automated anomaly detection systems

Now, if you directly jump on making a final data scientist resume, there are high chances that you might forget to include some of the duties which you performed.

In such a case, master data science resume will help you as it will be having all of the duties and responsibilities which you performed throughout your tenure in that company.

The master machine learning resume works like an outline of your final data science resume. So, since you already have all the information related to your data scientist resume there in the master machine learning resume, you can tweak your final data scientist resume according to the information in the master data science resume.

This process of making a machine learning resume will ensure to get you more interviews than you expect that you can get.

After you've compiled all the information in the master data science resume, you will start off with making your professional experience section.

  • First Draft for your Data Scientist Resume: In this stage, you will make the sections of the header, personal information, title, education, certifications, conferences, and publications as well as the section of additional information.

Hiration Pro-Tip: After making your master machine learning resume, do save a copy of it. It will be of a lot of help in the future when you'll need to update your data scientist resume as you change your career or switch to a new job.

  • Final Data Scientist Resume: In this stage, you need to do the following three things:

First, draft the skills section.

  • Pick out all the skills that you acquire from your professional experience section and the job description, then write them in the key skills section of your machine learning resume.

Second, compose your data scientist resume summary/data scientist resume objective section.

  • Look for the points that are the highlight of your career in your professional experience section and write them in the data scientist resume summary/data scientist resume objective section of your data science resume by rephrasing them a little.

Hiration Pro-Tip: Professionals with 3+ years of experience will make a data scientist resume summary section, whereas, entry-level professionals will make a data scientist objective section.

Third, highlight and bold all the important words, phrases and numbers in the sections of professional experience, certifications, conferences and publications as well as the additional information section.

Now, let us see in detail, how to write each section.

Data Scientist Resume Professional Experience Section

A professional experience section includes all the professional work that one has done in his/her career.

This section holds a lot of importance for those professionals who have extensive career history.

Use the below given format to write the professional experience section of your data science resume:

{Designation} | {Organization} | {Location (city, country pin)} | {Dates} (month & year)

Framing points in your Data Scientist Resume Professional Experience section

The above-given format will be followed by cause-effect points. Most people are able to tell what they did as Data Scientists, but they are unable to explain the impact that their work had on the business.

So, that's when cause-effect points come in. Cause-effect points are what demonstrates the impact of a persons works on the business. Let us see how to write the cause-effect points with the help of data science resume examples.

Data Scientist Resume Example 1:

  • Steering rapid model creation in Python
  • Built dynamic pricing models
  • Creating NLP models
  • Led the development of a performance assessment & pricing analysis platform
  • Deploying ridge regression model & LASSO solver to select the regularization parameters
  • Created multivariate regression based attribution models

The points in data science resume example one doesn't have the method of cause-effect used in them, hence they don't provide much information and the impact that the person had on the business.

Data Scientist Resume Example 2:

  • Steering rapid model creation in Python using Pandas, NumPy, SciKit-Learn & plot.ly for data visualization
  • Applied various machine learning techniques to build dynamic pricing models and maximize profitability
  • Creating NLP models for Sentiment Analysis & MapReduce modules for predictive analytics in Hadoop on AWS
  • Led the development of a performance assessment & pricing analysis platform by deploying k-NN Algorithm
  • Deploying ridge regression model & LASSO solver via gradient descent to select the regularization parameters
  • Created multivariate regression based attribution models using ad stock analysis from the digital marketing data

Now, by seeing data science resume example 2, you can see how using the cause-effect method to write the data science resume points is providing much more information around the impact that your work had on the business.

Bucketing/Grouping your Points in your Data Scientist Professional Experience section

The other elements that help bring out the best in cause-effect points are bucketing and bolding.

Let us now see with the help of data scientist resume examples, how bucketing and bolding makes a difference in the machine learning resume points.

Data Science Resume Example 1:

  • Steering rapid model creation in Python using Pandas, NumPy, SciKit-Learn & plot.ly for data visualization
  • Applied various machine learning techniques to build dynamic pricing models and maximize profitability
  • Creating NLP models for Sentiment Analysis & MapReduce modules for predictive analytics in Hadoop on AWS
  • Led the development of a performance assessment & pricing analysis platform by deploying k-NN Algorithm
  • Deploying ridge regression model & LASSO solver via gradient descent to select the regularization parameters
  • Created multivariate regression based attribution models using ad stock analysis from the digital marketing data

There is no use of bucketing and bolding in the points of data scientist resume example 1, which help in increasing the readability of the content.

Data Science Resume Example 2:

Data Visualization & Predictive Analytics

  • Steering rapid model creation in Python using Pandas, NumPy, SciKit-Learn & plot.ly for data visualization
  • Creating NLP models for Sentiment Analysis & MapReduce modules for predictive analytics in Hadoop on AWS
  • Deploying ridge regression model & LASSO solver via gradient descent to select the regularization parameters
    Statistical Modeling & ML Algorithms
  • Applied various machine learning techniques to build dynamic pricing models and maximize profitability
  • Led the development of a performance assessment & pricing analysis platform by deploying k-NN Algorithm
  • Created multivariate regression based attribution models using ad stock analysis from the digital marketing data

In data scientist resume example 2, we have made buckets of the skills used in doing the work as well as have grouped the points of works in which the same skills are being used.

Like we've made the bucket of 'Data Visualization & Predictive Analytics' and have written all the points pertaining to these skills under that bucket.

Same goes for the bucket of 'Statistical Modeling & ML Algorithms'.

Look at the data science resume example below to see how a professional experience section should look like.

Data_Scientist_Professional_Experience

Data Scientist Resume For Freshers

As freshers in the field of data science do not have relevant experience, they can't make a professional experience as they won't have anything to write in it.

So, now the question is: What will they make or do?

The answer is: Internship Section. Yes. Freshers in this field will make an internship section.

Internships are when you work in an organization as an intern to gain professional knowledge of your field while still not being a graduate, whereas, a proper job is when you work for an organization after graduating from college.

While still in college, students are likely to do a maximum of two internships. These internships help you gain the professional experience and hands-on professional knowledge of the workings of your chosen field. So, that is why the internship section holds a lot of importance in a freshers data scientist resume.

Including internships in your machine learning resume will give you the upper hand over the freshers who haven't done any internships during their graduation.

Having done internships shows the recruiter how serious you are when it comes to your professional life and that they are hiring a professional who takes his/her career seriously.

Use the following format to write your internship section:

{Name of the Organization} | {Location} (city, country pin) | {Dates} (in mm/yy-mm/yy format) | {Designation}

This section of the internship will also be written using the cause-effect method along with bucketing and bolding as explained in the professional experience section above.

Writing Data Scientist Resume Header

Now, that the master data science resume stage is over, let's proceed with the first draft machine learning resume. Start off this stage by making the data science resume header.

You must be wondering: What is a header and why is it important?

Well, a header comes at the top of your data scientist resume and it is made up of your name. Making a header ensure that your machine learning resume is being separated from hundreds of other data science resumes that have come in for the same profile.

Also, it gives your data science resume an individual identity of its own and prevents from being misunderstood as someone else's machine learning resume.

When writing your data science resume header, make sure that you give a single space between your first name and your last name. Spacing errors like that of double space or no space have a negative impact on recruiters mind. It will portray your carelessness when it comes to small details.

If you have a middle name, then write only the first initial of your middle name and then put a full-stop after it. Also, give a single space after the full stop and then write your surname. In addition to this, do not write your nickname in the header. Don't write something like "Cara 'Nitro' Delevingne".

Just simply write 'Cara J. Delevigne'.

When making your data scientist resume header, the ideal size of its text is between 14-16 point size.

See the data science resume sample given below to see how an on-point data science resume header should look like.

Data_Scientist_Header

In addition to this, you can instead use Hiration's Online Resume Builder to make your data scientist resume and that header absolutely hassle free. Our Online Resume Builder uses a pre-set, fixed font size to make the resume header.

Personal Information Section In Your Data Scientist Resume

In this section, three things are written: 1. Personal Mobile Number 2. Personal e-mail ID and 3. Current location

Personal Mobile Number

Write only one mobile number on which you are available 24x7.

Also, there is a proper way in which one needs to write the mobile number. There are certain rules to follow when writing your personal mobile number. You can't just go and scribble down that mobile number of yours.

The two rules that you need to follow while writing your mobile number are:

  1. Write the International Subscriber Dialing (ISD) code of your country followed by a plus sign (+) before your personal mobile number.
  2. Give a single space after the first five digits of your mobile number.

Writing only that number on which you are 24x7 available is important as a personal mobile number is the primary source through which a recruiter is likely to contact you.

Personal E-mail ID

Write only that e-mail ID in your personal information section which you use most often in case you have multiple e-mail IDs.

At this stage of data scientist resume making, you can even add hyperlinks to your social media websites like that of LinkedIn, Facebook, Instagram, etc. and personal websites or portfolios if you have any if they provide any support for the professional work that you have done so far.

Also, all the websites need to be up-to-date in terms of information and the information should be consistent across the websites.

Hiration Pro-Tip: Do not include personal information such as marital status, age, political views, etc. They are not to be mentioned in a data science resume.

The e-mail is the second way through which the recruiter might contact you. So, it is important to write only one e-mail ID that you use the most.

Current Location

This is the third thing to include in the personal information section. Here you will write the current location of your residence.

When writing the current location of residence, first write the city name followed by the country pin.

Take a brief look at the data scientist resume sample below to get a better understanding of how to write the personal information section.

Data_Scientist_Personal_Information

Customizing Data Scientist Resume Profile Title

Next in line comes the profile title section.

The profile title tells the recruiter the level at which you carry out your job responsibilities and duties. It also gives a broad level idea of your level of proficiency in your field.

The title is supposed to be the second largest text in your data scientist resume, written in between the font sizes of 12-14 points.

If a machine learning resume is missing a job title, then it is missing a crucial part of the data scientist resume. Hence, it is incomplete. If you send your data science resume without a job title, then it will get difficult for the recruiter to gauge for which profile you've applied for.

Writing a profile title makes the job of the recruiter easy and is a deciding factor for the recruiter to read your machine learning resume further or not.

Look at the data science resume sample given below to get a better idea about how a data science resume profile title looks like.

Data_Scientist_Profile_Title

Data Scientist Resume Education Section

The education section is one of the most important sections of the data science resume for a recruiter. It helps the recruiter to decide whether you are eligible for the job or not.

Use the following format to write this section:

{Name of the school/university} | {Location} | {Dates} (in mm/yy-mm/yy format)
{Name of the degree} | {CGPA}

The data scientist resume sample provided below will give you a better idea of how to write the education section.

Data_Scientist_Education

Data Scientist Certifications, Conferences And Publications Section

The second last section to make in the first draft stage is the certifications, conferences and publications section.

In this section, you will write all the certifications, conferences and publications that you ever got, attended or got published. Also, these should be those certifications, conferences, and publications that will add some value to your machine learning resume.

Use the format given below to write your certifications.

{Name of Certification} | {Affiliating Institution} | {Location} | {Date (in mm/yy)}

To write your conferences, use the below-given format.

{Your Role in the Conference}
{Title or Topic of Discussion}
{Conference/Forum Name}
{Date (in mm/yy) and Location}

Use the format given below for writing your publications.

{Authors Last Name} {Authors First Name} {Authors Middle Name or Initial of the Middle Name}
{Title of Article/ Chapter} {Name of journal, website, magazine, etc.}
{Year of Publication}
{Publisher or Issue Number} {Volume number} {Page Numbers}
{URL if its an online publication}

See the below-given data scientist resume example to see how the certifications, conferences and publications section should be like.

Data_Scientist_Certifications

Data Scientist Additional Information Section

The last section to be made in the first draft stage is the additional information section.

In this section, you will write the additional information about the languages that you know. For example: If you are fluent in speaking and writing English and Spanish, then you will mention it in this section.

Also, you will make this section of additional information only if you know how to speak and write more than one language.

To get a more clear idea on how to write this section, look at the data science resume sample given below.

Data_Scientist_Additional_Information

Illustrating Your Data Scientist Resume Skills

In the third stage of making machine learning resume, which is the final draft stage, the first section that you will make is the key skills section.

Writing the skills section in the final draft stage will give you more skills to write in your data scientist resume than you thought you have. Before writing your skills section, scan the rest of your data science resume once, throughly, to look for skills.

These skills will basically come from scanning the professional experience section.

After you're done writing the key skills section, bold the whole section.

Look at the below-given data science resume example to see how to write a key skills section.

Data_Scientist_Key_Skills

Technical Skills Section of Data Scientist Resume

If you have skills like that of SciKit-Learn, NumPy or SciPy then do not include them in the key skills section. These are considered to be technical skills, so make a separate section for them named 'Technical Skills Section'. It will be made in the same way that you have made your key skills section.

So, just like the key skills section, after you're done making your technical skills section, bold the whole technical skills section and then in addition to it, italicize the whole section as well. Italicizing the whole section will separate it from the rest of the data science resume and will make it more clearly visible.

To get a better idea, take a glance at the data scientist resume sample given below.

Data_Scientist_Technical_Skills

In addition to this, if you use Hiration's Online Resume Builder to make your machine learning resume, then you'll have the options of adding bar graphs and pie charts to make your skills section.

Look at the data science resume sample given below to see how you can demonstrate your skills using bar graphs and pie charts in your skills section.

Data_Scientist_Skills_Picture

Personalizing Data Scientist Resume Summary Section

The data scientist resume summary section is written at the very end of the data science resume making process so that you can refer the rest of the machine learning resume and pick out the points that are the highlight of your career and then add those points in the data scientist resume summary section after rephrasing them a little.

You need to use the data scientist resume summary section wisely by telling the recruiter what you can do for the organization by explaining how you used your data scientist skills to benefit the previous organization.

Look at the data scientist resume sample below to see how to optimize your data scientist resume summary section.

Data_Scientist_Summary

Furthermore, You can use Hiration's Resume Reviewing Service to get your data scientist resume professionally reviewed by the industry experts to check your data science resumes complete consistency.

Data Scientist Resume PDF

If you want to have a data scientist resume PDF then you should definitely make your machine learning resume at Hiration's Online Resume Builder as after making your data science resume at Hiration's Online Resume Builder, you can download unlimited PDFs of your data scientist resume.

So, what are you waiting for?

Go and make your machine learning resume at Hiration's Online Resume Builder Now!

Data Scientist Resume Doc

If you want a doc template for your data science resume then opt for Hiration's Resume Reviewing Services, where you'll get two free machine learning resume doc templates, as well as your data science resume, will be reviewed to match the following parameters:

  1. Reliability (achievements and skills backed with quantifiable values)
  2. Cause vs. Effect relationship
  3. Readability (to pass the 6-sec test)
  4. Achievement based points over responsibility based points
  5. ATS Compliance
  6. Compliance with industry norms
  7. Global compatibility
  8. Performance assessment (How well a candidate has performed to get shortlisted)
  9. Conversion Scope
  10. Design Compatibility

So, opt for Hiration's Resume Reviewing Service Today!

Key Takeaways For Your Data Scientist Resume

  1. Ensure that your data scientist resume summary does not exceed the limit of 3-4 lines. Write only those points in the data scientist resume summary section which highlights your most distinct skills and achievements across your career.

  2. Usually, the data scientist resume summary section is the first section that a recruiter sees. Therefore, it is important that it is crisp and includes only the most important point in it.

You can begin the data scientist resume summary by writing the number of experience you hold and then mentioning your filed followed by your proficiencies.

  1. For example: '7+ years experienced data scientist with a passion to solve real-world business challenges using data analytics.' Continue in this manner and mention some special hards skills and some achievements that proved your proficiency in the previous organization.

  2. Since the space in the data scientist resume summary section is limited, mention only those skills and achievements which really make you stand out from the other applicants. And with this also ensure that the skills and achievements that you write in the data scientist resume summary section are relevant to your target profile.

  3. Tailor your professional experience section according to the job description. Make sure to mention the skills written in the job description in your machine learning resume.

Also, if you have performed any of the duties written in the job description, then ensure that you write those duties in your professional experience data science resume points.

  1. Make the key skills section just after your data scientist resume summary, followed by the technical skills section.

Making the key skills section is of paramount importance as these days the resumes are first passed through the Applicant Tracking Systems (ATS) and after passing the ATS test, only do they get on the table of the recruiter.

  1. The ATS scans the resume for the keywords that are written in the key skills section. If the key skills section will be missing, then your resume will get rejected at the stage of ATS testing itself.

Also, only write hard skills in the machine learning resume which you can substantiate in the interview and avoid writing soft skills.

  1. Include your key skills across your data scientist resume and not just in the key skills section. Writing keywords throughout the data science resume increases your chances of passing the ATS test.

  2. There are chances that the companies in which you have worked previously are not known to the recruiter. So include a one-line description of your company under the company name in your machine learning resume. In this description, try to sell the company to the recruiter.

  3. In this description, you can include some numbers around the number of employees the company had, its revenue, etc. Basically, anything that lets the recruiter know that you've been working for a good company. Do the same for all the companies that you've worked for.

Still got more questions around your data scientist resume? Send your questions at team@hiration.com and our data scientist resume experts will get back to you.