5 Habits I Learned From Successful Data Scientists at Microsoft

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1. Make learning and self-improvement a priority.

Microsoft didn’t send me an email to attend their virtual summit neither did they send me a VIP invite because I still use Hotmail till today.

Does anyone here still use Hotmail?

The truth is, if I had not desired to learn more and expand my knowledge I wouldn’t have had an idea a free summit organized by Microsoft was in progress.

The technology behind Data Science is vast, especially in these present times where high numbers of connections are automated.

Continuous learning and improvement are paramount for Data Scientists looking to stand out from the crowd of other qualified data professionals.

How to apply it:

As many already know Data Science is not a static field. Look at job descriptions, find out what skills most employers are looking for in a data scientist, and compare with your resume.

Are you lacking these skills? Identify your weak points and work towards improvement.

With the majority working a regular 9–5, remote learning has proven flexible and effective. Engage with online courses, documents, videos, podcasts, research papers, and blogs relating to data science and other essential fields.

2. Build a professional data science network.

The virtual conference had lots of highly qualified Data Scientists, no surprise there but I wondered how they got to this huge stage of landing a gig with Microsoft, so I did a little research.

I went on LinkedIn and checked each of their profiles, and the one thing they all have in common is they all have over 5 thousand connections on the platform.

The cliché of Data Science being a solo adventure is pretty dated now. I know, the freedom of deploying models, the joy from creating beautiful animations to your visualizations, or predicting analysis through your instincts.

All these sounds amazing, but there is a high tendency you’ll need a few extra brains to make analysis quicker and efficient.

Teamwork is very important especially now that Data solutions are evolving by the minute, you will need to connect with like-minded professionals with vast knowledge of other technical fields.

Apart from that, new networks and connections bring you closer to new information relating to internships, freelancing jobs, and lucrative career offers.

How to apply it:

Due to the upsurge of Data Scientists in major sectors, numerous opportunities are created every year for professionals to connect and network with other professionals with mutual interests.

When next you go for an interview, regardless of the result, ensure you make a professional connection with the interviewer — ask questions, tips, resources, and show curiosity.

Career opportunities, collective problem-solving skills, and career endorsements are essential benefits of building a strong professional network.

3. Effective data scientists are good readers.

I know what you’re thinking; Data Science is all about figures, stats, and coding, what am I supposed to read?

Well, the concept and implementation behind the basics of Data Science are all gotten from plain words.

It’s not just about models and programming languages; it is paramount that you understand the inner workings of your profession.

The truth is if you are depending on the tricks and experience you’ve gathered from your previous or current job, there are massive tendencies that you will remain professionally stagnant.

“Reading research papers will greatly help data scientists keep track of trends and developments within their industries.”

Saurabh Jha.

How to apply it:

There are hundreds of quality research papers, books, articles, and magazines exhibiting valuable Data Science resources to educate yourself and expand your knowledge about certain concepts in your field.

Before I moved on to get my Data Science certification, I learned most of the programming languages and analysis tricks from blog posts.

Apart from the technical aspect, reading write-ups about productivity, career tips and personal development will redefine your mindset towards positivity and the right attitude to work.

4. Be active in Data Science communities.

Early last year, I had this drive to share what I’ve since I began my journey into Data Science. Facebook groups and telegram pages didn’t work on my path due to the lots of scams and malware circulating most social platforms. A Trojan horse almost stole a project I had been working on for over 6 months.

Heads-up: Never click any random link you see on Facebook groups unless you know the source.

Regardless of your status or experience, as a Data Scientist, you should be willing to assist. Open to solve a particular task, find and publish data sets, and coach younger professionals in the industry. With the high rate at which Data Science is expanding, more individuals are diving into the pool of Data-related fields, intending to diversify and expand their technological intellect.

However, it is necessary to help support future engineers, analysts and scientists, to foster effectiveness and maximize impact in others.

How to apply it:

Become a pioneer, write valuable create blog posts, research papers, and articles in Data Science forums. If you have a knack for speaking, you could start a podcast or a YouTube channel dedicated to sharing your experience and easy-fix hacks to simple data challenges.

5. You can’t escape it — Develop excellent coding skills.

The most controversial Data Science questions on Quora:

From my findings, I realized that most Data Scientists are looking for ways to escape the coding aspect of Data Science and it worries me that lots of people are looking for the easy route to success.

Of course, not everyone likes coding, but the sad thing is they are not willing to learn.

A Data Scientist should at least have basic knowledge of programming languages such as Python, JavaScript, and R, as most Data-related tasks are built on solid coding ethics.

How to apply it:

There are tons of high-quality online courses covering the fundamentals and advanced aspects of numerous programming languages. Do your research and find out the necessary skills you need to stand out in the industry.


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