5 Tips to Create a Job-Winning Data Science Resume in 2021

5 Tips to Create a Job-Winning Data Science Resume in 2021


You are about to create the best data science resume out there, but first: Data Scientists are unicorns. However, most of your overburdened hiring managers don't know this. They can't see the wonders you make with data-driven insights.It's all Greek to them. You need to cram all your data science superpowers onto your data science resume to prove that you are the best candidate out there for the open data science job. So, how do you write a perfect data science resume that your hiring managers can understand? This article will reveal the top 5 tips to create a perfect data science resume and a lot more.

Best Data Science Resume Tips

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Data Science Resume: 5 Expert Tips to Write The Best One

Before we unlock the secrets to writing a perfect data science resume, let's understand the market demand for data science job roles and if creating a perfect data science resume is worth your time and effort. According to the Bureau of Labor Statistics, data science expertise will steer 27.9. % increase in employment by end of 2026. This shows there is a growing demand for people who have the required data science skills. Data scientists are among the highest paying jobs of 2021. The median annual salary of a data scientist is $94,280, and the hourly wages are expected to keep growing. One more factor that adds to the popularity of data science careers is the shortage of professionals in this field. Many colleges and universities around the globe have created data science courses to help more future data scientists enter the market faster, but it will still be a while until we are able to close the gap.  The good news is that you don’t necessarily need a degree in data science to start your career as a data scientist. Professionals with degrees in IT, computer science, math, and even physics can try their hand at data science. So, if you’ve always been interested in working with large and complex datasets, you can start preparing for a data science career transition right now. And we’ll help you get your data scientist resume ready to help you land your first data science job interview.

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1. Rethink the Structure of Your Data Science Resume

You know that the traditional way to organize the information in your resume is to put everything in chronological order. You can either start with your education and proceed to your experience or list your jobs first and then briefly touch upon your education later. Whatever option you choose, all the information in your data scientist resume should be structured chronologically as shown below in the data science resume sample -

Data Science Resume Example

Image Credit: Indeed

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But even though this format is the most common, it doesn’t mean it is always the best when it comes to presenting your data science skills and experience. And, it won’t come in handy if you previously worked as a robotics engineer, and now you decided to switch careers and become a data scientist. There are two other resume formats that you can choose from depending on your experience and professional profile:

  • Functional Resumes. In this kind of resume format, you focus on your skills and abilities first. This resume structure de-emphasizes your work experience and focuses on your skills and accomplishments right away. You can use the functional resume structure if you have gaps in employment due to family reasons, job loss, etc. Here’s a data science resume example with a functional structure, where expertise comes first:

Data Science Resume Sample

Credit: Monster

  • Combination Resumes. This is a mix of chronological and functional structure. Your resume starts with a list of core data science skills, and then you put your job experience in reverse chronological order. This structure is the best choice if you want to highlight the reasons why you are the best fit for the data science job. This resume structure doesn’t require extensive lists of skills and job experience – just put the skills related to the job and work experience relevant in data science as shown in this data science sample resume:

Data Science Resume Examples

Image Credit: Resume Genius

Which structure should you choose if you don’t have any work experience in data science?

Anyone preparing a data science resume entry-level should choose a functional resume structure. It allows you to highlight your data science skills in your resume in-depth. You can still list your previous work experience just for reference, but the main focus will be on your skills, abilities, and achievements.

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2. Complement Your Experience with Achievements

Another common data science resume practice is to add a list of tasks that you’ve performed in a particular job role. The best way to do this is to have a mention of few data science projects on resume and link these projects to the accomplishments. The below sample resume for data science for a data analyst job role gives a general idea of what a person’s responsibilities were and which abilities formed a result of their accomplishments.

Here’s an example:

 

Data Analyst

Google, 1600 Amphitheatre Parkway, Mountain View, CA

  • reported on KPIs across web properties
  • operated a logistic regression model
  • ran cohort analysis for product managers

 

While simply listing your responsibilities is still a viable option, it makes your experience lack personality. But if you want to optimize your data scientist resume to actually attract the attention of potential employers, try to refocus your responsibilities on the achievements that you’ve accomplished while performing your day-to-day tasks.

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Let’s restructure our data science resume example from above with the focus on achievements:

Data Analyst

Google, 1600 Amphitheatre Parkway, Mountain View, CA

  • managed a team of junior data scientists; built a reporting system with the team to track KPIs across all the company’s web properties
  • build a logistic regression model for the SEO team to improve keyword optimization, which brought a 13% increase in website visitors
  • regularly ran cohort analysis with the product management team, which boosted the company’s revenue by $500,000

 

As you can see, there’s a drastic difference between the first and the second data science resume examples. The first one sounds oversimplified and looks as if you took these responsibilities from a random data science resume template.

However, the second one is more detailed and resembles your personal work experience. If you reformat your resume this way, it will definitely stand out and make you seem a better fit for the job than other candidates.

3. Highlight Transferable Data Science Skills

Transforming a list of responsibilities into a list of achievements is a great idea. But what if you don’t have relevant responsibilities or achievements to highlight in your data science entry-level resume? What if your previous jobs were only freelance or remotely related to data science? No worries, you can still have the high ground and show that you are the best person for the job by bringing forward your transferable data science skills.

In our combination data science resume example from the first section, you might have noticed that the list of skills is not limited to technical or hard skills typically for a data scientist. There are also other soft skills like leadership, crisis management, collaboration, and problem-solving. These are just a few examples of transferable skills – a set of abilities, which can come in handy in a variety of jobs and occupations.

The list of transferable skills also includes:

  • Teamwork and management
  • Proficiency in a foreign language
  • Written and verbal communication
  • Organizational skills
  • Time management skills
  • Negotiation skills
  • Delegating
  • Research skills

Including transferable skills in your resume for data science is not just for beginners. In fact, if you put organizational or soft skills next to your knowledge of technical data science skills,  your resume will only get better since it shows your versatility as a professional.

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How do you know which transferable skills an employer is looking for?

Indeed, the list of transferable skills may vary depending on the job. The best solution is to go through each data scientist job description and to choose keywords that indicate transferable skills:

Data Scientist Resume based Data Science Skills

Image Credit: LinkedIn

The employer in the example above is looking for a person who can work independently and has strong verbal and written communication skills. You can highlight these skills in your data science resume with no experience to show that you fit the employer’s requirements. But don’t forget to add some proof of how you developed these skills to avoid making empty claims.

4. Make A List of Data Science Tools You’ve Mastered

Another important tip to create the best data science resume with no experience is to add a list of data science tools that you’ve mastered apart from the must-have skills and experience.

If you take a closer look at the example from the previous section, you’ll see that the employer is asking about the experience working with tools like Hadoop, Hive, Spark, DR, etc. If you know how to implement data science and machine learning projects using these tools, highlight your abilities in your data scientist resume.

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There’s a list of basic tools a data scientist needs to know how to operate:

  • SAS – a tool for statistical operations.
  • Apache Spark – a solution for batch processing and stream processing.
  • BigML – a tool used for processing machine learning algorithms.
  • MATLAB – a tool that helps data scientists simulate fuzzy logic and neural networks.
  • ggplot2 – a data visualization solution.
  • Jupyter – an open-source IPython solution for writing live data science code and create data visualizations.

Even if the employer is not asking for experience with any of these data science tools, adding them to your resume will give you a competitive advantage. It would also be great if you added how you mastered these tools and which of your job responsibilities were connected to them.

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5. Customize Your Data Science Resume for Each Data Scientist Job Description

In the previous two sections, we talked a lot about browsing the job description to find the important keywords that describe the job position and adding them to your resume for data scientist jobs. This leads us to the most important point in our little guide – you need to tailor your data science resume to each employer’s needs.

The first thing you should start with is your data science resume objective – it should resemble what the employer is looking for. In the data science resume example below, the employer is looking for someone who can work with complex datasets, do research, and develop analysis, forecasting, build and prototype analysis pipelines

Data Scientist Resume Example

 

​Image Credit: LinkedIn

Thus, if you decide to apply for this data science job, your resume should reflect what this data science job description is looking for :

Sample Data Science Resume objective: Data scientist with 5+ years of experience in managing large and complex datasets for machine learning, running research and development for large corporations, and building forecasts based on big data.

The same keyword research is necessary to organize your job experience and qualifications that you’ll list on your resume for data science. Let’s say an employer prefers someone with a Ph.D. in Statistics, Applied Mathematics, or any other related field or experience in software development:

Data Science Resume Objective

Image Credit: LinkedIn

If you highlight these keywords in your job resume, you’ve increased your chances of landing a data science interview from them.

Even though data scientists are still rare to come across, it doesn’t mean that your resume should have baseless claims in it. So, try to tailor your data science CV to every employer to show that you are the best fit for the job.

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Optimizing Your Data Science Resume: Key Takeaways

Starting a career in data science is exciting – there are so many multinational companies looking to hire data science expertise. Besides, many of them are willing to help you learn the necessary skills if you’re just starting your career in data science. Regardless of where you find yourself, if you want to get a job in data science, you need to start by optimizing your resume for these data science jobs. Here’s what you need to do:

  • Rethink the Structure of your Resume - It will depend on your skillset and the experience that you can offer a potential employer.
  • Add Achievements instead of simply listing your responsibilities - Your achievements are proof of your competencies. Besides, they make your resume look more personalized.
  • Put forward your transferable skills - This can especially come in handy if you’re an entry-level data scientist.
  • Create a list of tools you can work with - Employers often look for people who have experience with certain tools. Regardless of whether you have this experience or not, create a separate list of tools you’ve mastered to make a stronger case for your resume.
  • Personalize your resume for each data science job description -Show them that you’re the best person for the job by picking the main keywords from job descriptions and adding them to your resume.

Author: Dorian Martin is a writer and contributing editor at the academic writing site Get Good Grade. He also specializes in resume writing and helps students who are just starting the career paths create powerful CVs.

 

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