Finding a new job can be stressful and can involve many time consuming steps, with the first step being writing a resume and a cover letter. In this blog post, I want to share my own experience with writing a resume as well as provide valuable resume writing tips that I think eventually helped me land a data science job in Germany.

Resume Template

Apparently every resume starts with a template. There are plenty of templates available on the Internet, but, in my view, it's crucial to choose ones with a clear and well-organized structure. Personally, I've used a paid template from resume.io, but I would advise to use this free classic resume template from Yale University, which you can download here.

Resume Structure

Having an organised structure in your resume is essential, because it makes it easier for the reader to quickly navigate through your experience, skills and education. Typically, a good resume includes the following content sections:

• Header with you contact details
• Education
• Work Experience
• Skills

And then there are optional sections that are nice to have to show your unique personal and professional growth:

• Awards and accomplishments
• Publications in relevant professional magazines
• Licenses and certifications
• Personal relevant projects

You can consider including an optional Summary section immediately after the Header with your personal information. This section quantifies your relevant experience and highlights its value for the desired position. Experts recommend keeping this part concise, typically around 3-5 lines.

When writing your resume, it's crucial to use clear descriptive headings for each section and include experience information directly related to the position you're applying for. If you're including your honours, achievements, leadership experiences, personal projects, ensure their relevance to the role.

Regardless of the resume structure and sections you choose, it's advisable to prioritise them from the most relevant to the least relevant. This approach effectively showcases your strengths in a clear and compelling manner. I have illustrated different ways to structure your resume below:

In my own resume I have used the following order of sections:

• Header with my personal details
• Experience with my employment history
• Education including my bachelor degree and extra curriculum online courses
• Publications in a mathematics magazine
• Personal projects in data science and software development
• Skills including both hard and soft skills

An important thing to remember is to keep the content of your sections short and to the point, so it can fit on just one or maximum two pages. In my case, I've managed to summarize everything onto a single page.

As a source of inspiration for your resumes you can use the following examples:

1. Resume and a cover letter examples from Stanford University
2. Resume and a cover letter examples from MIT

Also keep in mind that if you have some experience that you cannot fit onto a single page, you can always consider adding this information to your LinkedIn profile, which the HRs can visit by clicking a link in the Header section of the resume.

Resume Content

Now let’s dive a little bit deeper into the content of the sections.

Header Section

All resumes start with a header and an important topic to consider is whether to include your photo on the resume or not. While many sources strongly advise against adding an application photo (particularly in the US), it could still be effective in certain situations. For example, Karlsruhe University of Technology  has the following line in the “Application Tips” section:

Hardly any company representative will tell you openly, but: A sympathetic, friendly and professional photo can have a positive effect on the evaluation of your application.

In my own experience, I've tested resumes both with and without a photo, and I didn't notice a big difference in terms of the response rate.

The rest of the information is the section is straightforward:

• Your first and second name
• Your phone number and e-mail address
• Link to your LinkedIn
• Your current place of living

Work Experience Section

When it comes to filling out the work experience sections with your own information, I find it important to go with a bulleted PAR (Project, Activity, Results) statements approach as it really helps showcase your strengths in a clear way:

Just like with the order of sections, experts suggest putting your most impactful on-the-job achievements first. When creating PAR statements, start with "Action verbs," and don't forget to include job-specific keywords and terminology.

There are plenty of lists of "Action verbs" floating around the web, which however tend to be quite alike. Here's a good list of action verbs by MIT that you can check out for reference.

I've learned that paying close attention to keywords and terminology is very important. Based on my experience, many recruiters have a fairly basic understanding of what a data science job entails, so they're specifically looking for certain skills and keywords in your resume. That's why I would recommend providing as much context and information about the tools you've used as possible. For example instead of writing:

efficiently mined data from external and internal sources

You could go for:

Wrangled 10 TB of trading data stored in Hadoop distributed system using Scala to remodel and visualise 15 previously inaccessible datasets

The second version of the text expands more on the exact type of data you’ve been working with as well as the technologies that you’ve used, in this case Hadoop and Scala.

Another thing that I find useful doing is, try to quantify the results of your work so that readers could easily see how much of an impact you’ve made and could understand your ability to solve real-world business problems. Instead of simply writing:

Utilised Spark to perform distributed data wrangling for a large volume datasets.

it would make sense to provide the actual numbers and re-write the text the following way:

Developed a Spark pipeline to perform distributed data wrangling on 10TB of data, which reduced the total processing time by 20%.

Resume Formatting

The resume template that I’ve shared in the beginning of the essay already follows the recommended formatting rules. You may find extensive guidelines about these rules in multiple sources, personally I like this guideline by Yale University.

As mentioned in the beginning, a basic one-pager resume will have:

1. Clearly defined content sections
2. Header section with your name, contact details and link to LinkedIn
3. List of the positions you have worked along with
   (a) your title or role, location, and dates and
   (b) 3-4 bullet points with PARs for each position
4. Education such as
   (a) your bachelor degree and
   (b) your master’s degree if you have one
5. Skills such as
   (a) languages, with proven level of knowledge if available
   (b) programming languages  
   (c) working with server infrastructures like AWS or Azure
   (d) etc.

Don't forget to review your resume for grammar and syntax errors, and feel free to use LLMs like ChatGPT to improve your text.

Final Personal Notes

While your academic background and work experience are undeniably important, I personally find resumes that include references to GitHub or Kaggle especially advantageous. This allows recruiters and especially hiring teams to easily verify candidate's skillset. Stay tuned for our next blog post, where we'll provide a list of relevant data science hackathons in Germany and worldwide.

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Thank you for reading. 

Alex P

P.S. Looking for a data science job in Germany at a tech company with interesting challenges, pay and work culture? Check our curated list of data science jobs in Germany.