Data science has lost none of its cachet in recent years; companies all over the world very much need data scientists to crunch enormous datasets and provide insights. Job opportunities abound. But does that demand actually make it harder for a tech pro to land a data-science job? Hilary Mason, a data scientist and founding CEO of New York City-based Fast Forward Labs, sees “a ton of people asking for data scientists.” Her company’s newsletter has likewise experienced an increase in job postings. Large corporations such as Ford Motor Co. have also “increased the number of data scientists we hire,” according to Laura Kurtz, the auto-giant’s manager of recruiting. “We recently created a new data analytics group to understand and make better use of them.” Ford relies on data scientists for everything from human resources (to develop better strategic workforce plans) to manufacturing (to study process efficiencies and throughput). The company is hiring data workers from across the whole experience spectrum, including recent college graduates. But not every company is hungry for more data scientists. Kaggle.com, which organizes data-science competitions and jobs, recently cut seven of its approximately 20 jobs. (Despite its shrinking staff, the firm still runs dozens of contests, some with pretty significant payouts; that’s in addition to posting newsworthy datasets such as Hillary Clinton’s email collection, stored in a SQL database.) Kaggle isn’t alone in the data-competition department: DrivenData currently runs seven different data science contests, most of which focus on improving conditions in far-flung parts of the globe. Texata.com offers an annual Big Data business-world championship, specifically designed for college students. Numerous hackathons make use of data-science techniques, as well. If you want to enter this still-vibrant field and land a job, here are a few suggestions from the pros:

Understand What You’re Getting Into

Not all data science jobs are alike, and not all positions carry equal prominence at all companies. Dave Holtz, writing a post for online-learning site Udacity, has put together a great list of suggestions on how you can evaluate different job openings and company types. His post also suggests eight different skills that you should have in your tool-kit, such as statistics, data visualization, and basic software engineering. Also on the list: advanced calculus and linear algebra.

Online Tutorials

Mason feels the hiring market has matured to the point where “companies are a bit more aware of what skills they actually need, rather than asking for the kitchen sink. Over the last few years, companies have gotten better at hiring data scientists, both in defining the skills they actually need and in interviewing and supporting data scientists once they join a team.” If you’re interested in brushing up on your day-to-day data skills, look at some of the online tutorials at Datacamp.com, where you can find more practical exercises such as how to use R and Python scripting for large datasets.

Participate in a Contest

Another way to hone your skills is by participating in a data-science contest. Kaggle’s CTO has put together a list of suggestions on how to win such competitions. These include entering alone (rather than as part of a team), using some kind of data visualization tool, and doing frequent iterations on whatever solution you come up with. If you’re interested, take a look at the next GlobalHack contest, held in the fall in St. Louis, with a total purse of a million dollars in various prizes.

Look Inside

Look inside your own company to see if you can spearhead a data-science approach to some of your thorniest issues. “A number of companies get to the point where they have a lot of traffic (and an increasingly large amount of data),” said Udacity’s Holtz, “and they’re looking for someone to set up a lot of the data infrastructure that the company will need moving forward.” This could be the best opportunity; after all, you should already know your own business.