Is there a definition for the “X factor”? As most of you will know, we aren’t referring to the famous television show, but a personality trait, X factor usually refers to that indescribable quality that adds to the successful tangent of a person.
For example, Data Science is one of those blessed fields where an individual can achieve a unique balance between human interaction, technical knowledge and career growth. However, to “have it all” they require the strong bonding and feeling of community among each other. We have all heard about the power of pull and what it can do to careers at large.
That is why, even if data science is the sexiest job of the 21st century, a strong sense of community goes a long way for these talented bunch of individuals. This week, Analytics India Magazine explains how data scientists should go about cultivating their own community from scratch and foraging lasting bonds with fellow data scientists.
Be Active On Social Media
Social media — be it Twitter, Facebook, Instagram, or LinkedIn — is the perfect option for persons who are not comfortable in sharing their thoughts and ideas face-to-face. With the help of pictures, posts and sharing knowledge, data scientists can showcase their expertise and share knowledge. On the other hand, social media is a very powerful tool that transcends boundaries and brings together people and information from across borders. This is a place where data scientists go to learn about what’s happening, what’s trending, and what’s in the news.
Use GitHub To The Fullest
A crucial part of data science jobs is to be able to code, and GitHub serves as a perfect platform to access the coding skills and display hands-on ability to solve problems. There a few ingredients that make up for a good data science portfolio, some of them are a few medium-sized data science projects, showcasing the problem-solving abilities, which can be done by highlighting practical problems on GitHub. As the importance of having a good GitHub profile has been stressed out so many times, there are often questions on what potential employers are looking for and what a good GitHub account generally looks like.
With data science being a relatively new field, it is easy to get overwhelmed by the number of resources available online. We often hear about data science enthusiasts kick-starting their journey with online content but that’s only enough to teach you the basics in this field. This is where meetups come in handy. As online learning can also be a disjointed experience, data science meetups offer an excellent opportunity for networking and hands-on skills building sessions for professionals.
Participate In Hackathons
Now, more than ever, we are seeing a pattern where young professionals want more challenging jobs and more interesting work, especially in the Emerging Tech sector. And hackathons have turned out to be a very valuable source of answer to both employees as well as employers. According to a survey conducted by AIM, over 64% of organisations have at one point of the other conducted hackathons for ideation and creating a healthy sense of competition among its employees. In fact, over 44% of the employees we interviewed said that their organisation held hackathons at least once a year.
Noted industry events like the upcoming conference Cypher are a great melting pot of interesting personalities from across the country. Given a vast range of topics covered over three days in five parallel sessions, Cypher sees a generation of content from the best minds in the industry like no other conference. Here, data scientists have a great chance of meeting peers, potential employers as well as competitors under the same roof.
Write For Noted Portals
Technical content writing is now becoming one of the quickest ways to express yourself online. With noted portals looking for fresh takes on sought-after topics related to artificial intelligence, machine learning, data science and IoT, among others, more and more people are choosing this route to express themselves online. By expressing yourself online, you will:
- You’ll gain confidence in your work
- You’ll reach out to the data science community
- You’ll validate your expertise
- You’ll create opportunities
- You’ll not only be a data scientist, but you’ll also be a storyteller
- You’ll build your brand
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