3 Unique Ways to Get a Job in Data Science
All too often, job seekers focus too much on building their skill sets without thinking about the softer skills of howto get a job in data science in the first place.
It doesn’t matter how good of a data scientist you are — you won’t get a job unless you know how to get a job.
What does that mean, exactly? It means that in addition to all of your technical knowhow, you need to know more about how to build a good resume showcasing your skills, how to prepare for your long-term goals, and how to get a jump on data science jobs that don’t exist — yet.
[Related article: How to Balance Work and Learn More About Data Science]
Learn how to make the most out of your existing skillset
It’s rarely easy jumping into a new field, industry, or completely different career path, so data science is no different.
“No matter what field you’re in, if you are a creative problem solver who wants to understand the big picture, give data science a try,”. said Triveni Gandhi, data scientist at Dataiku. “Every industry can benefit from an analytical approach and your experience will become a boon to your understanding.”
“Diversity in data science — in gender, racial, and background — is critical to improving our models and ensuring that they serve the users who engage with them,” she continues. “It’s an exciting time to be a data scientist; collaboration and open source development is flourishing and anything seems possible.”
Try to stand out
No, don’t try to be a flamingo or wear a rainbow-colored suit to your interview. Be a better candidate however you can. Sasha Tomic, Associate Dean for Strategy, Innovation and Technology of Boston College’s Woods College of Advancing Studies, outlines three ways you can do just that — especially if you’re just starting out:
- Work on your network. Attend meet-ups, talk to people in the field, try to reach to people in your target company. If you find a fellow alumnus doing what you would like to do, reach out to them for an “informational interview” in which you aim to find out more about the job. LinkedIn is your friend in this endeavor, and do not be shy. In these conversations, try to find out what obstacles their teams/companies face in the field in which you are interested.
- “Say not what a company can do for you, say what you can do for the company”. So, once you have networked and found out about opportunities and challenges, which of these challenges can you solve? Once you have determined this, then make sure that in your cover letter you avoid waxing rhapsodic on how great of an opportunity this job is for you. Focus on how you can contribute to the team and the organization.
- Buy Dale Carnegie’s “How to Win Friends and Influence People.” It is a worthwhile read that will not take a long time and it is worth every second you spend on it. Learn how to interact with others in meaningful ways.
Prepare for jobs that don’t exist yet
AI is scaling in unique ways; no longer are we just using data for analytics or automation, rather, it’s being used to completely transform entire industries. “Take nanopharmacy for example. Now that we can create machines that operate at the nanoscale and that could conceivably deliver medicine at the molecular level, how do you define, collect and manage the necessary data to make this work?” said Christopher Bishop, Chief Reinvention Officer of Improvising Careers.
“While keeping up with the latest in Python is important, being aware of the business problems that future-focused companies will be trying to solve is really the key to a successful career,” Chris continued. “At the end of the day, companies want help using data to generate attributable revenue, take market share, improve productivity, and enhance efficiency — no matter what business they’re in.”
[Related article: Here’s Why You Aren’t Getting a Job in Data Science]
What’s next?
One person’s road to a career in data science won’t be the same as another person’s path. To stand out, you’ll need to use your background and spin it towards data science, prepare for emerging markets, and stand out from the bloated pool of other data science experts.
For those who have already gotten their career off the ground — what would you add to this article? How did you stand out? Comment below and let us know!
Editor’s note:
ODSC brings its reputation for cutting-edge content to Manhattan and gives you the unique opportunity to build your career at the same time. With expert-led trainings on the latest tools, technologies and frameworks in data science combined with resume reviews, mentored talks and a career expo, Immersive AI this June 28–29 in NYC will be an event you don’t want to miss. Register here!
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