Despite an increasingly constant demand by employers to having a team of data science professionals possessing great tact of work, attracting the best companies can not only be extremely difficult but also intimidating to a job seeker . Our jobs platform has over the past few months recorded a rise in the skillset demand for soft digital skills in Machine Learning and programming jobs from some of the big companies in Africa. However, even as applicants attempt to enter this increasingly competitive field, many are still struggling with the same challenge: nailing the data scientist resume.
Crafting the perfect data science resume will not only effectively market your skills when applying for your next data science job but also give you confidence in your achievements. And while many struggle writing a brief summary of individual strengths and achievements, here are a few tips to help you keep your resume crisp, clear and attractive all at the same time.
Put In-demand skills first
You probably enrolled for an Intermediate Data Science course during your career to polish your skills in Python programming or you probably took an executive masterclass in supply chain analytics, and you can now derive insights from huge data blocks for your projects. Well, make this the top of your skillset list.
Talent acquisition managers don’t usually have time to go through the resume looking for the skills. You should therefore consider putting it at the very top. Hook them to quickly see your qualifications and already begin thinking of your employability.
Also, employ your understanding of the need to use Data Visualisation tools in personal projects. Do not make an endless bullet list for your skills but you should instead go for something different by looking at online template designs or get a designer to neatly arrange your skills on your resume. Make your document catchy.
Give a detailed description of your achievements
Your main goal is to list your relevant professional achievement and not giving a narration of everything you have engaged in while in your programming career. Write down professional data science – related accomplishments for example; ‘Attended an executive Data Analytics one- on- one coaching session by Predictive Lab’ or, participated in a Data Science boot camp conducted by Predictive Lab. Let the Talent Acquisition Manager analyze your achievements and at the same time see that you meet the existing demand of the organization.
Secondly, include numbers, as a quantifiable accomplishment demonstrates your impact much better, e.g. “Analyzed marketing processes with custom machine learning algorithms to generate $2,000 in savings” is more impressive because of the numbers. After all; you are applying for a data job, right? So use the data. Lastly, use only one sentence per each achievement. Your resume should fit in one page, so be careful and limit each achievement to one sentence.
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Explain your non-technical skills, do not just list them
For data scientist, soft skills really matter because one must be able to tell a story while giving insights. Thus, explain them well rather than just jotting them down. Only remember to keep them short and concise just as in your achievements. Do not story tell. Here is an example to help you;
Teamwork and written communication – Worked with a team of 10+ marketing team, applying data analysis models to identify patterns in customer data.
Predictive Lab Student make a consultation during an Introduction to Data Science Class
Match Keywords in the Job Description
It’s important to know that most hiring managers use keywords in job descriptions. Some of the keywords in the data science industry revolve around qualifications, certifications, skill name, technologies etc.
Spread out the keywords all through your resume. Do not stuff them as it will make you look too obvious instead play around with the words naturally to avoid looking like you are trying too hard to match what they were looking for.
Building your digital presence
Having good tips on how to write a good Data Science resume does not get you your desired job. You still need to keep polishing your existing skills by engaging in learning platforms such as our 4IR Club or subscribing to our newsletter to get the latest insights in the world of Data Science.
As you wait to get recruited, keep on building your job profile on different job placement sites, polish your Linked In presence as interviewers nowadays usually look at your Linkedln Profile to see what you post, build your Github and Kaggle profile; you should upload your personal projects and code on this platform to help recruiter rate your technical ability and finally follow and join Data Science Communities on Linked In, Quora, Twitter and Discord to engage with experts in your field in questioning, answering and solving data science related probes.
Predictive Lab CEO Networking with fellow Data Scientists during a meet up in Dubai
There is no perfect CV, but there is a better way to show your work. The goal of this article is to not only give you advice on these main sections of your CV, but to also give you motivation on what new ideas you can come up with yourself. Above all, learn to focus on being yourself, highlighting the proudest accomplishments of your career and finding something creative and unique that can make your resume stand out.
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https://masterclass.predictiveanalytics.co.ke/ page that allows you to browse through our Data Science Courses