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How to Network and Build a Personal Brand in Data Science


SpringBoard shares some ideas on how to network and build a data career, as taken from a new guide they have put together on the topic.



By Roger Huang, SpringBoard.

At Springboard, we’ve created a comprehensive guide to breaking into data science careers. During part of the research for the guide, we developed a list of resources to network and build a personal brand in data science, which became a section of the book. Here is the excerpt:

Network and Build a Personal Brand in Data Science

Once you have learned the skills and developed a strong portfolio, the next step is to connect with people who can help you leverage those strengths into a data science job.

Building your network among data scientists will substantially increase your odds of breaking into the field. Many of the best opportunities aren’t posted on job boards. Solving challenging real-world problems will enable you to build a portfolio and a personal brand, and land a job based on that.

Finding a Mentor

Perhaps one of the highest-value networking activities you can pursue is finding a mentor who can guide you as you seek and pursue a data science career. Somebody who has been in a hiring position can tell you exactly what companies are looking for and how to prepare for interviews. She can also introduce you to other people in the data science community, or in the best of cases, even end up hiring you!

Perhaps one of the highest-value networking activities you can pursue is finding mentor who can guide you as you seek and pursue a data science career.

What most people don’t get is that mentorship is a two-way street, and you can always create value for your mentor in different ways, whether it’s sharing your story, or giving them some perspective on problems they see. Mentorship is a relationship where you can build value for yourself in a professional context -- but never forget the golden rule of relationships: you get what you give.

We’ve seen the benefits of mentorship first-hand at Springboard. In all of our courses, students are paired with a mentor from the industry, which leads to significantly better outcomes through increased accountability and motivation.

Meetups and Conferences

In this section, we’re listing some of the popular events and conferences we know of. With just a bit of searching, you can find great data science events in your area. These are great places to meet fellow aspiring data scientists and pick up the jargon. At some of these events, you will get to hear from and build connections with established data scientists, and even unearth hidden job opportunities.

Meetup speaker

A big data meetup with a speaker presenting.

At events and meetups, you’ll network with fellow data scientists, and interview for hidden job opportunities.

Conferences

Strata Conference

The Strata Conference is a big data science conference that takes place worldwide in different cities. Speakers come from academia and private industry: the themes tend to be oriented around cutting-edge data science trends in action. Practical workshops are provided if you want to learn the technology behind data science, and there are plenty of networking events.

KDD (Knowledge Discovery in Data Science)

KDD or Knowledge Discovery in Data Science is another large data science conference. It’s also an organization that seeks to lead discussion and teaching of the science behind data science. Membership and attendance at these conferences offers an awesome way to contribute to growing trends in data science.

NIPS (Neural Information Processing Systems)

NIPS, or Neural Information Processing Systems, is a largely academic data science conference, which is focused on evaluating cutting-edge science papers in the field. Attending will give you a sneak preview of what will shape data science in the future.

Meetups

We’ve listed the major conferences where the data science community assembles, but there are often smaller meetups that serve to connect the local data science community.

The San Francisco Bay Area tends to have the most data meetups, though there is usually one in every major city in America. You can look up data science meetups near you with Meetup.com. Some of the largest data science meetups, with more than 4,000 members, are SF Data Mining, Data Science DC, Data Science London, and the Bay Area R User Group.

Most data science meetups are organized by influencers in the local data science community: if you really want to make a splash, you should consider volunteering at a data science event.

Most events follow the same format, with an invited speaker who gives a talk, and then a networking period where everybody networks with each other (usually over beers). The general data science meetups will often have an industry talk where somebody will delve into a real-world data science problem and how it was solved. Specialized data science meetups, such as Python groups for data science or R groups, will often focus on technical tutorials that teach a specific tool or skill.

You should introduce yourself to the local data science community! Many of the best career opportunities are found by talking to people passionate about a certain field, many of whom will be with you at a data science meetup.

Other Ways to Network

We live in a digital world, so you shouldn't feel confined to offline networking! Some of the best data scientists are on Twitter. There are also a number of great data science podcasts and newsletters to follow.

Podcasts such as the Talking Machine interview prominent data scientists. Partially Derivative offers drunk data-driven conversations. The O’Reilly Data Show is the equivalent of a graduate seminar delivered in podcast form.

You’ll also find blogs and online communities such as O’Reilly, Kaggle and KDnuggets that will help you connect with data scientists.

Make sure to check out the relevant communities on Reddit and Quora, where you can engage in trending data science discussion. And you’ll always find a lot of great programming resources and pieces on Hacker News!

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