Comprehensive Guide to Crafting a Perfect CV in Data Science
Introduction
The Data Science job market is highly dynamic. Despite the abundance of job openings that appear regularly, there is a high influx of candidates. A single job posting can attract several hundred applications! Therefore, landing a dream job can become a very lengthy process.
There are several ways to increase your chances of success in the job market. Obviously, one of them is your Cv. While the CV is only one part of the entire recruitment process, it can make a significant difference.
An accurate, visually appealing, well-structured, and concise CV has great potential to attract recruiters.
This article contains useful tips to refine your CV and transform it into a valuable asset that will help you get noticed in the job market.
The recommendations in this article are based on my own experience in Data Science and my perception of how to make a CV stand out. You might not find some of my advice productive, and that is perfectly normal. Nevertheless, I did my best to present and explain my arguments.
01. Choosing a right template
Choosing the right template is a fundamental step in creating a good CV. There are various templates available on the Internet that simplify the creation process. However, the problem with many of them is that they focus too much on visual aspects or fancy styling, which may be completely unnecessary for simply showcasing your experience and skillset.
Moreover, the structure of many templates cannot be modified, making them inflexible. In particular, if you wanted to mention a project you had worked on in the past, you might want to insert a link to the Git repository, provide another link to the deployed app, or even add an image with a short description. With standard CV builders, organizing such a structure can be problematic.
As a result, if you wish to organize your CV sections differently, you might end up spending more time searching for a template that better matches your preferences.
Finally, many people repeatedly use the same templates, and at some point, it becomes crucial to stand out from the crowd.
For these reasons, I would like to introduce several excellent tools to help you create a professional-looking CV.
LaTeX
LaTeX is a popular text typesetting language. It is a state-of-the-art tool often used in machine learning papers, scientific research articles, and documents requiring extensive mathematical notations. Not only does LaTeX allow you to elegantly write complex equations and organize content beautifully, but it can also be set to automatically number sections, pages, or create annotations, which is a great time-saver when dealing with large documents.
Like other typesetting languages, LaTeX has a special syntax that can be converted into high-quality PDF documents using third-party engines with LaTeX support. LaTeX offers a large number of libraries and directives, allowing documents to be customized in many different ways.
In practice, crafting a CV using LaTeX can be a time-consuming process. Without extensive experience in LaTeX, even simple tasks, such as inserting an image and aligning it correctly with the text, can become a challenge. For that reason, the next section introduces a different tool to simplify the CV creation process.
Overleaf
Overleaf is a popular website built on top of the LaTeX ecosystem, primarily serving two main purposes:
- Overleaf is an online editor that can compile and display LaTeX documents.
- Overleaf offers a rich collection of templates, including visually appealing presentations and high-quality CVs.
Many of the available CV templates can be easily edited directly in the browser. Here are a couple of examples of great-looking templates for CVs:
Figma
Figma is software primarily used by designers to create application prototypes, design systems, and various tasks related to user interfaces. At its core, Figma does not require specialized domain knowledge, making the process of creating basic interfaces easy for users without prior design experience.
Like LaTeX, Figma offers a large collection of CV templates created by other designers, which can be easily modified within the interface. In this regard, Figma has a simpler learning curve than LaTeX since it is a visual tool.
Final advice
While Figma is great, I would still recommend using a combination of LaTeX and Overleaf for crafting CVs, as these tools are widely used in Data Science and by many machine learning researchers to publish scientific papers. Therefore, a CV made with LaTeX automatically conveys a more professional look in the field of Data Science.
As a bonus, being able to create a CV with LaTeX implicitly signals to recruiters or Data Science team members that you have experience with LaTeX, which may be especially valued if you are applying for a research position.
02. Section order
In most cases, CVs should include the following sections:
There is no single consensus on the order of sections. Nevertheless, based on how humans typically read text, it is reasonable to assume that most recruiters read a CV from top to bottom. That is why it is generally recommended to list sections in an order where higher sections have greater priority than the lower ones.
A CV should tell a logical story about yourself, and the order in which you place the sections affects how recruiters perceive it.
Experience & Education
One of the most popular pieces of advice is to place the "Experience" section above the "Education" section if you have already had commercial Data Science experience in a company. If you are a student or have recently graduated, then it makes sense to position "Education" above "Experience".
Projects
If you have completed a project outside the scope of commercial experience that you are genuinely proud of, it is also a good idea to include it in your CV. If I had to place the "Projects" section, I would position it below "Experience" and "Education".
Despite the potential value of the project you completed, I assume that most IT companies prioritize hands-on commercial experience or a certified university diploma over an unknown project you have done on your own.
Skills
For "Skills", I cannot give a specific recommendation, but most of the time, they are located at the bottom of the CV. Sometimes I have seen examples where skills were outlined at the top of the CV. In my opinion, both options are valid. Nevertheless, if you believe that you have an outstanding and extensive skill set that could strongly impress a recruiter, it might make sense not to follow the general pattern and place "Skills" near the top.
03. Photo
There are two kinds of people:
- Those who claim that a person's photo should be included in a CV.
- Those who recommend not including a photo in a CV.
As for me, I belong to the second group. I believe that the presence of a photo in a CV creates an implicit bias, which may lead a recruiter to prefer another candidate, even if there are better candidates in terms of professional skills and experience.
Of course, for certain job types, especially in the modeling industry, facial features matter significantly. However, in other job sectors (including IT), I believe that facial attractiveness should not create any bias or influence the recruiter's choice.
Personally, I do not have anything against those who include their photo in their CV. However, I have genuine respect for individuals, especially those with attractive faces, who consciously choose not to include their photo in their CV, understanding that it may cause an unfair bias in the selection process for others. Even such a small gesture makes the world around us more equal and fair.
By removing your photo from your CV, you contribute to a fairer selection process and slightly reduce selection bias.
For that reason, if I were a recruiter, I would prefer candidates without profile photos.
If you still want to show off your face, place it on your personal website or portfolio and leave a link to it in your CV instead.
04. Size & format
As a rule of thumb, a CV should not occupy more than a single A4 page. This makes sense, as recruiters generally spend only a few seconds taking a first glance at your profile. If you can condense all the sections onto a single page, there is a greater chance that the recruiter will notice valuable information about your candidacy.
If you want to showcase more about your profile than just a single page, a great alternative would be to create a personal website where you can provide the necessary details. You can build the website yourself or choose from one of the available online constructors.
Personally, I really like the Carrd service, which allows users to create simple, fully responsive websites and deploy them. Moreover, there are many prebuilt templates that can be adapted to beautifully display your CV.
When it comes to format, PDF is a clear winner. It is flexible and very convenient to use. I would not recommend sending a CV in Microsoft Word .docx format, as this can result in inconsistencies and display issues based on the software version used.
Another useful tip is to appropriately name your CV, for example: ____CV_.pdf. This helps recruiters easily filter and sort applications, as they may receive CVs from hundreds of applicants for a single job posting, many of which may have generic names like _cv.pdf, datascientist.pdf or even unnamed.pdf.
For improved readability, also make sure to set balanced margins between the page edge and the CV content.
You can go even further by including the name of the company you are applying to in the filename. This way, your CV will be a little more personalized, which can create a slightly better impression of your candidature.
I would also like to highlight the importance of checking for the absence of any grammatical or syntax errors in your CV. The way you write your CV partially reflects your personality and whether you pay attention to small details.
05. Experience
General information
For general information, it is usually recommended to specify the names of the companies you previously worked for, along with the location and the period of employment. This is the most common advice.
Many people may ignore this advice, but I find it useful to also specify the job duration. While writing only the job period (i.e., May 2023 – September 2024) is acceptable, including the job duration (i.e., 1 year 4 months) allows for an easier and quicker estimation of the total number of years of experience a person has.
Tasks
One standard way to describe experience is to list several points consisting of short sentences that provide a good perspective on the projects and technologies you worked with in the past. It is better not to include long texts, as they are harder for a reader to process. Instead, present the key information using a simple list of bullet points.
A good strategy is to back up your points by providing real numbers that demonstrate the impact of your work.
Another popular approach is to list points by using the X-Y-Z framework originally proposed by Google:
Here are some examples:
Do not worry if you cannot measure the effect of your work. In some situations, it may not be possible, especially if business metrics are difficult to quantify.
Providing 4–5 key points about your commercial experience at each company you have worked for in the past is a good strategy.
Description consistency
It is important to stick to a single format when describing your experience in your CV. As an illustration, it is a common practice to begin each point mentioned in the experience section with a verb in the Past Simple tense.
If you are writing your CV in another language to apply to a company located outside an English-speaking country, make sure to find out the most suitable format used there.
Contrary to the recommendation of starting every sentence in the Past Simple tense for a CV in English, a much more common practice for a CV in French, for example, is to start each sentence with the infinitive form of a verb.
Rich vocabulary
To make your CV more engaging, another effective strategy is to avoid repetitive phrases and use synonyms. Not only does a rich use of synonyms showcase stronger language skills, but it also adds variety to your CV, helping to keep it interesting for the reader.
Additionally, if you are applying to large tech companies, it is likely that they use automated software to preselect relevant CVs. Appropriate use of synonyms increases the chances that your experience will utlimately be considered more relevant to job requirements and will help you pass the preselection process.
The diagram below shows synonyms that you can use.
06. Projects
If you have any personal or pet projects, they have amazing potential to elevate your CV to another level! Ideally, you should provide:
I want to emphasize the importance of having a deployed application. This aspect can distinguish your CV from many others. Even if the project is outstanding but not deployed, it will be difficult for a recruiter or anyone reviewing your CV to ultimately understand and visualize the final results. On the other hand, almost nobody will spend time looking through your code in Git.
Humans are visual creatures. That is why project visualization makes the application more attractive in the eyes of others.
Another great aspect of app deployment is that it demonstrates that you likely possess some degree of DevOps and web development skills, which are valuable for machine learning engineers.
Additionally, it shows that you can complete a project all the way to the final step, which is undeniably a good quality to have.
Finally, if you do not want to spend a lot of time on UI or DevOps aspects, I recommend using Streamlit. It is a fantastic open-source Python framework designed for the rapid development of data applications, with robust support for many visualization tools. Streamlit has a low entry barrier, as the simplest visualization applications can consist of just a few lines of code! Furthermore, Streamlit provides an online platform to deploy your applications.
07. Skills
Nowadays, there is a large number of technologies that Data Scientists are expected to be familiar with. When listing them in your CV, it is important to present them in a manner that is easily readable for a recruiter. One of my favorite ways to organize skills is to split them into categories.
Following the same principle for sections, it is better to place skill categories in order of their relative importance.
As you can see, I have also listed known technologies related to frontend and backend development. While they do not directly correspond to standard Data Science stacks, I personally perceive them as a great bonus if a candidate is familiar with them. Not only does this demonstrate a wide skillset, but it is also especially valuable in startups and small enterprises where a single developer is expected to work on various stages of Data Science projects.
Redundant skills
A common error I observe is that people sometimes redundantly specify technologies in their CVs that do not provide any significant value.
As an example, for Data Scientists, there is little reason to explicitly point out that you know how to use Jupyter Notebooks or Google Colab. Without a doubt, these are necessary skills to have, but they are too basic and only require a few minutes to master. Furthermore, 99% of Data Scientists know how to use interactive notebooks, so you will not impress anyone by explicitly mentioning this.
It would be nearly the same if a taxi driver was proudly announcing to his passengers that he knows how to drive a car.
Another scenario is when people specify tools that serve the same purpose and functionality. As an illustration, there is no need to mention that you know GitHub, Bitbucket, and GitLab – they are almost identical centralized version control systems (VCS) in terms of usage, providing the same features except for the more advanced ones (e.g., CI/CD). In most cases, specifying just one of them is sufficient. I would even recommend listing only Git on your CV. The reason is that even basic knowledge and experience with Git imply that you are likely familiar with centralized VCS.
The table below demonstrates other examples of redundant technologies that should be omitted or reduced in quantity.
Listing a lot of beginner skills can have the opposite effect, suggesting that you have included them merely to fill your CV, primarily because you do not possess advanced technologies. A better option would be to omit these skills and focus on putting or learning more advanced tools.
Rating skills
Some people like to rate their skills in their CVs. In particular, it is common to encounter a list of skills a person has, with a bar representing how strong or weak a particular skill is.
The problem with these bars is that each person perceives the represented scales differently. For example, in the image above, the knowledge of the PyTorch framework is rated at 50%. This information is very abstract and does not convey whether a person is able to:
- train neural networks with PyTorch
- efficiently use various framework classes
- fine-tune a model for a custom task
- understand how backpropagation works in general.
The same problem applies not only to PyTorch but to many other technologies as well.
The ideal option would be to list concrete tasks one can accomplish with a given technology (as in the example above with PyTorch). However, since it is important to keep the CV brief, I believe the best approach is to simply name the technologies in your CV that you feel confident enough to use in solving common problems.
Languages
On the other hand, for human languages, I recommend specifying your knowledge level. This is because, contrary to technical skills, it is easier to assess a person's language proficiency. The most common way to specify language knowledge is by using the CEFR (Common European Framework of Reference for Languages). This framework contains a scale of six levels: A1-A2, B1-B2, and C1-C2. Each level corresponds to the minimal competencies a person is expected to have in order to claim proficiency at that level.
You can specify language skills by either using the CEFR scale or by using descriptive words that indicate your proficiency level.
My advice would be to include in your CV only those languages in which you have a level starting from B1 (or even B2), except for English and the language used in the company you are applying to.
For many people, this advice might seem counterintuitive. Nevertheless, here is my logical explanation behind it:
- If you apply to a company where the primary language is native to you or in which you are fluent, then it does not provide any value for an employer to see that you have A2 proficiency in another random language. Even if someone in the company knows that language, it would still be problematic to have conversations with them.
- Most international IT companies require at least a B2 level of a foreign language, depending on the country where the company is located. Otherwise, working with a lower language proficiency in a commercial environment would be complicated.
- Without a doubt, English is the dominant language in the IT industry, especially in Data Science, where research articles, documentation, software, and the best resources almost always appear in English. That is why even a B1 (or even A2) level of English can be valuable, especially if a person can read and understand most of the technical content.
As you can see, the reasoning here is similar to the one discussed in the section above about redundant skills. Why do I focus so much attention on this? The answer is simple: employers are only interested in the skills that can provide real value to them. That is why, when speaking of skills, I like to cite this personal saying:
Either remove it or improve it.
This concept applies not only to creating a perfect CV or finding a job but also to life in general. Being able to present yourself concisely while focusing on the most important aspects is correlated with higher self-esteem, rather than getting lost in insignificant or unrelated details.
08. Personal Qualities
Some people like to proudly list their top qualities, such as:
- responsibility
- discipline
- time management
- communication
- punctuality
My question to them is: what is the point? By default, a good candidate is expected to possess ALL of these essential personal qualities. There is no valuable information for the recruiter when you specify how responsible or punctual you are. Moreover, people can write about how great they are, but in reality, it could be the complete opposite.
If you still want to leave a positive impression based on your personality and achievements, a much better strategy would be to provide concrete examples. The image below shows points you can mention in your CV:
When it comes to professional success, remember the following saying:
Actions speak louder than words.
09. Hobbies
While it might be interesting to find out what you enjoy doing in your free time, nobody will hire you just because you are a great soccer fan, enjoy watching movies, or like playing games. Given that, I recommend that everyone generally avoid including their hobbies in their CV.
The only scenarios in which I would approve the inclusion of hobbies in a CV are the following:
- If your hobbies include high-quality pastimes, such as reading, going to the gym, learning languages, or helping animals.
- If your hobbies are directly related to Data Science, such as mentoring others, creating machine learning tutorials, or writing a blog.
Be cautious when listing "non-intellectual" pastimes. For instance, a recruiter might have a negatively biased opinion of you if you include playing computer games as a hobby in your CV. As crazy as it might sound, some recruiters may indeed assume that you will be distracted by games during working hours, which could negatively affect your productivity.
# 10. Adaptable CV
In the modern era, although it is quite common to conduct IT job interviews online rather than being present in the office, it is still important to be prepared for any scenario. Regarding in-person interviews, I have noticed that interviewers sometimes print the candidate's CV and go through it during the interview.
For that reason, you should take care of the following details:
- If you have a colorful CV, make sure that it preserves its good look when converting it to grayscale.
- Remember that links are no longer clickable when printed, so ensure that they are appropriately replaced or mentioned in the document.
- Leave enough margin space between the content and the page edge, as printed sheets can sometimes have slight offsets.
Conclusion
In this article, we have explored valuable tips to enhance your CV, which are applicable not only to the field of Data Science but also to the software engineering domain.
However, it's essential to remember that a CV is not the sole component of success in your job search. Even with a well-crafted CV, you may spend months seeking that desired position. Additionally, the selection process is inherently subjective; different individuals may perceive your CV differently, leading to biases in the hiring process.
Nevertheless, this should not discourage you from putting forth your best efforts in areas you can control, ensuring that you present your candidature in the best possible way.
Resources
All images unless otherwise noted are by the author.
