Personal Qualities Section in a Resume Summary. What to Write?

What do you write in the “Personal qualities” section of your resume, and how seriously do you approach the filling of this particular section? It is possible that the qualities you point to are indeed your key benefits. But before you send your resume next time to your employer, make sure it doesn’t list the same as hundreds of other resumes.

Finding out what others are writing is very easy. On the job site, look in the “Resume” section, and not in the usual “Vacancies”. According to the observations of employees of HR services, about 90% of applicants write the same thing about personal qualities – based on what the employer wants to see in the applicant for the position. In addition, when many people say that they are executive, proactive, have excellent communication skills, a kind of devaluation occurs, and employers stop taking this section of the resume seriously. You can trust resume writing services to do this.

So What Should You Write?

The main thing is not to try to excel just to get attention. The list of personal qualities-advantages should:

a) reflect the characteristics of your character and style of work, which you consider to be your strengths;

b) take into account the specifics of the vacancy. For example, honesty is important for the cashier, attentiveness for the air traffic controller, and for the sales manager the ability to tell about the product so that there is a line for it.

What Qualities can be Noted as Strengths in the Resume?

Systems thinking

We mean by this the ability to see the situation as a whole, to understand what link you, as a specialist, occupy in the general process of production or sale of goods and services. And this is important not only for people applying for leadership positions. It is also useful for the seller to understand what customer demand is and why promotions are held. Systems thinking allows you to make more informed decisions, see the future, be able to determine priorities when making decisions.

Ability to maintain high productivity throughout the working day

It is important for an employer to understand that you radiate energy not only in the morning after a cup of coffee, and not only when you have a brilliant idea. Much more important is consistently high labor productivity, which does not fall after stressful situations or too nourishing lunch.

Ability to adequately perceive criticism and respond to it

This is actually an important quality, and the employer will appreciate if you really have it. The workflow is much more productive if you can listen to criticism and learn from it.

High concentration of attention and the ability not to be distracted by personal affairs during the working day

The employer is unlikely to make the employee happy with the bonus, who now and then speaks with family members on a cell phone or tweets and posts on social networks. Emphasize that at work you are only doing work – and you will benefit.

Ability to provide information (proposals, reports, results of analytical work) in an accessible and visual form.

The leader has to look through many sources of information, and how much information is presented in them determines how much time the leader will spend to study the material and see the “grain” in it. Therefore, the ability to present information, to present it in a structured manner, without “water”, using diagrams, pictures is an absolute advantage.

Summary

Do a little self-analysis and look for the answer to the question: «How do I compare favorably with the specialists of my profile? What special qualities do I have?» Writing a resume, and let it work for a successful job search!

Why is Finding a Job in Data Science so Hard?

It’s common knowledge that data scientists are high in demand. The profession offers high-income potential and job flexibility and satisfaction – meaning not only are data scientists in high demand, but it’s also an appealing job prospect for many people.

Those who have decided to pursue a career in data science have probably found themselves in a state of disappointment.

While all job hunting is tedious and often difficult – what with constant cover letter writing and endless interviews only to never heard from the company again – it seems particularly difficult for data scientists.

So why is finding a job in data science so hard?

There are several reasons why you might be struggling to find a job in this – what’s supposed to – high-demand profession. Below are just a few:

Companies don’t know what they need

When it comes to recruitment agencies, as data science is such a new role, most staff aren’t quite sure what they’re supposed to be looking for. Similarly, companies that think they need data analysis aren’t particularly sure what they need and what they should be advertising for.

It can be difficult to know what types of skills the best candidate will have with any new role. Most HR teams or hiring managers aren’t entirely sure what a data scientist is, and what their day-to-day role will look like.

With this in mind, it might be a case of searching for different terms on job sites. Data science jobs may be listed under other roles, so it’s always worth broadening your job search to look at each job in more depth to understand whether it’s right for you.

The interview process is missing the mark

Just like how the recruitment process isn’t clear, the interview process can also miss the mark. Without knowing the proper skill set a data scientist needs, the interviewer can neglect to ask the right questions to find out whether candidates have the right abilities needed for the job.

This can be unfair to the candidates who have more specialized qualifications.  So, if you’re struggling to nail the interview process for a job you know you could do well, it could be a case of ‘it’s not you, it’s them…’

The struggle to calculate ROI

When it comes to hiring new staff, it’s all about what the company can afford and how beneficial the new employee will be. As such, companies will be required to calculate the ROI (return on investment).

As with any job, the hiring and training process costs a lot. And the value of a data scientist isn’t immediately provided once they start the job. As such, it can be difficult for businesses to calculate ROI for hiring a data scientist, and as a lot of businesses are impatient, this can significantly impact whether they are open to hiring someone in the first place.

Practical vs. Academic knowledge

While the previous three reasons finding a job is so hard aren’t directly related to you as a candidate, that’s not to say you couldn’t also be the thing that’s stopping you.

Those that have dedicated their time to academics can often lack the practical knowledge required for the working environment.

While the basics will generally stay the same, the world of data science is constantly evolving. There’ll be new findings and different algorithms, meaning a career in data science will require you to update your skills and knowledge constantly.

To set yourself up for success, you might want to consider taking an online Masters in Applied Statistics so that you can understand more about how to apply your academic skills to the practical world. Being able to adapt to different events and showing the hiring team your practical skills for problem-solving could make the difference and gain you your dream job.

You’re struggling to sell yourself

As with any job search, it’s all about how you market yourself to prospective employers. Despite having all the right experience and qualifications, the perfect candidate often slips through the gaps – leaving them feeling like they’re missing something or did something wrong during the interview.

More often than not, highly qualified, and skilled applicants lack the confidence to sell themselves. And sadly, the interview process is all about marketing your talents.

Before heading to your next interview, consider working on your confidence or prepare answers that prove you know your stuff and you’re not afraid to flaunt it. Check out these interview tips for help, too!

Final Thoughts

So, as we all know, finding a job is never easy. It can be nerve-wracking, tiring, and long. Let’s also not forget about the emotional drain it can have: With every rejection letter or for every business that completely ignores your application, your confidence can take a hit. Are you really good enough for this job? Should you be applying for roles at a lower pay grade? All of this doubt can make the process even more upsetting and unenjoyable.

However, it’s worth remembering – especially when it comes to jobs in data science – that you’re not always the issue. You might have all the skills and experience you know you need, but the recruitment agencies don’t know what they’re looking for. Similarly, companies might not understand the need for data science and quickly become impatient when they don’t see a significant ROI quickly. This all makes finding a job more difficult.

So, if you’re struggling to find a job right now, don’t lose hope. Take this time to focus on building your own portfolio and finding opportunities to develop practical skills. You can also take time to work on selling yourself and refining your interviewing skills. 

Lastly, you can also try to market yourself and create your own dream job. While some companies don’t realize they need data science, this means there’s the chance to create the job from scratch. All you have to do is believe in yourself and find a way to prove how valuable you will be.

Good luck!