Landing your data science job – Part 1: Preparing for your application

Data science job positions have witnessed an increased growth of 1287% from 2013 to 2018 in the UK (according to the Royal Society report). With an average salary of £64,376, there are forums exploded with threads about how to break into the industry.

The hiring process, however, can be long and overwhelming. It can take months of learning, building your profile, tens if not hundreds of applications, and numerous rounds of interviews before landing your first job. As a leading headhunter focusing in the analytics field, here are our step-by-step guide for breaking into the industry.

1.Understand the role you are applying for

Data science(alongside AI) are now buzzwords and there is an explosion of in terms of people want to work in Data Science,, which is dubbed as the sexiest job of 21st century by Harvard Business Review. However, there are many roles within the Data Science industry. The most common one is:

  • Data Analyst
  • Data Architect
  • Data Scientist
  • Data Engineer
  • Data Visualiser (Data storyteller)
  • Machine Learning Engineer
  • AI Engineer
  • Computer Vision Engineer
  • Marketing Analyst
  • Credit Risk Analyst
  • Business Analyst
  • Business Intelligence Consultant

All of those above roles involves using data in different ways to serve different areas in a business. For example, about 88% of Data Scientist has an advanced degree and they tend to apply machine learning knowledge. If you are a recent graduate with a strong background in mathematics or statistics, your chance of getting an offer will be much higher if you apply for data analyst roles(more explanations here). Credit risk analyst, meanwhile, roles normally require to have relevant experience in finance and risk modelling(more about that here).

2.Build your data science portfolio

Finished your homework about your dream roles? It is time to build your digital presence online. Most hiring managers and talent acquisition teams nowadays will look at your Linkedin before sending you the invitation to a telephone interview. So it is important that you have polished your online presence. Here are some tips to boost up your online presence:

  • Create and polish your Linkedin: Most employers will look at your Linkedin if they want to invite you to their interview. Your Linkedin profile should be updated and show relevant experiences to roles you are applying to. For example
  • Update your code on Github: Known as where programmers building their ego, Github portfolio is a free PR tool where you can show your impressive data mining, cleaning or data analysis skills. There should be at least three well-documented projects showcasing techniques that can be highly relevant to your future positions. For simple projects, try Datacamp ( from £21 a month) or Dataquest projects ( from £20 a month). If you think your data science is on point, join Kaggle contests. Being a top 3 in a Kaggle contest can be an amazing selling point for your application.
  • Blogging your journey of data science study: Creating and Sharing your finding with data science community is a great way to build your credibility as an upcoming data scientist.
  • Attend meetups and conferences: Start building your reputation in the data science community by attending events to enhance your technical skills or to learn about new trends of the industry. There will certainly experts(or your future managers) lurking in the corners in all those conferences so attending them will surely a good opportunity to connect and learn from them

Things to avoid:

It takes a long time to build your online presence. You need to connect to the quality, right people on your field on Linkedin, as well as slowly building your Github profile. Employers will be impressed if you have shown progress in learning new technology over a long period. We recommend the process should take place at least 4 months before you apply for your data science jobs.

3.Prepare your Resume and Start Applying Early

You think your online presence is good enough? You need to start building your resume and apply now. Every recruiter or hiring manager has different criteria to judge whether or not a candidate is suitable for the role. In order to overcome those challenges, your CVs should be short, concise and customised to fit for the role you are applying for. Some general rules are:

  • Don’t include irrelevant information in your CV: A recruiter can spend time reading hundreds of CVs per day, and in order to stand out from that, don’t put items like your wife names or how many children you have in your resume.
  • Qualify your achievement: Show your achievement in number, as it is easier to understand and it will immediately capture the attention of the recruiters.
  • Make sure you have the keywords: A lot of big firms use ATS software to screen the CVs and Cover Letter, especially for positions with hundreds of applications. In order to pass the CV Screen Round, you need to make sure you have the necessary keywords in your
  • Apply early: If you are a recent graduate, applying as soon as possible before the deadline of the job. Keep updated with the job post of the companies you want to work for.

Things to avoid:

  • Apply from generic common job portals: It is easy to log in on your job portal and apply after a long day at work. However, it is really hard to distinguish yourself from anyone else
  • Apply to every job with the same CV: There are different requirements for different roles. Despite the same job title, you should customise your CV to show not only skills but relevant knowledge of the industry you are applying to.

In our next blog post, we will discuss further what your necessary actions to pass your data science interview and you should do after each interview. Stay tuned!

For more useful recruiting tips, visit our blog or listen to our podcasts. You can also browse more data science jobs or contact Dan for more senior opportunities.