If you’re not looking to bolster your marketing organization with a data scientist or two already, you will be soon enough. And when you start the search, you’ll probably find it a difficult one.
But search you must. On the eve of a digital society producing 400 zetabytes of data, the opportunities presented by better data understanding and processing ability are too great to ignore. And the dangers of waiting while others get ahead or trying to tackle data on that scale with insufficient tools and talent could lead to disaster.
Here’s why you should be looking to hire a marketing data scientist sooner than later, and how to go about it.
Data Science vs Analytics
Analytics has been a staple of marketing programs for some time now, and interest continues to grow. However, many business leaders remain confused about the difference between data science and marketing analytics, considering them as two terms for the same field.
In reality the two are distinct and equally important, albeit complementary and often codependent. The differences can be nuanced:
- In general, analytics focuses on precisely determining what, exactly happened already and tying that to corollary trends. Analytics is usually more certain and definite, drawing from hard historical data.
- On the other hand, data science is more oriented toward determining probable causal relationships to some degree of certainty and predicting what will happen in the future as a result of some trend. By its very nature, data science comes with some uncertainty and much of the field is focused on minimizing that while still offering prescriptive guidance to business decisions.
Having only analytics talent or data science professionals in your organization will leave you with an incomplete (and often deceiving) picture. You’ll need both on your competitive intelligence team to successfully navigate tomorrow’s business environment.
Image from Data Scientist Insights
The Data Science Talent Gap
Interest in the field of data science has grown steady over the last five years as the associated roles have become more established and their value has become more evident.
Click Here for the Most Up-To-Date Chart from Google
The skyrocketing career opportunities across many fields and industries inspired Harvard Business Review to call the role of Data Scientist “The Sexiest Job of the 21st Century.”
But as the demand for data scientists has grown, the pool of qualified talent in the evolving world of big data hasn’t kept pace. In an emerging field with very specific skill requirements, there aren’t enough qualified individuals to go around. That difference is a large part of what will drive the shortfall of nearly 200,000 unfilled advanced data jobs by 2018.
The importance of having access to top-tier data scientists to forecast the future and guide critical business decisions is evident. With talent scarce and competition high, it’s crucial to be able to identify the right professionals for a marketing organization and put yourself in a place to attract them.
Key Traits for a Marketing Data Scientist
What must your data scientists do? I like Harvard’s definition for its Data Scientist course:
- Wrangle the data (gather, clean, and sample data to get a suitable data set).
- Manage the data in a way that gives you access to big data quickly and reliably.
- Explore the data by creating and testing a hypothesis using the scientific method.
- Make predictions using statistical methods such as regression and classification.
- Communicate the results using visualization, presentations, and interpretable summaries.
Data Genius with a Hint of Marketer
Unfortunately, sourcing a scientist isn’t as easy as grabbing an analytics guru in finance or R&D and dropping them in an agency or marketing department.
It’s one thing to find someone who can crunch the numbers and spit out reliable insights and predictions. It’s another to find someone who can do that and still function as a marketer, in a marketing environment.
Your ideal data scientist will speak marketer as fluently as they do statistician, and be able to translate from one to the other for the benefit of their organization. But at the very least, you want them to have a broad foundation you can quickly build on with a little training and experience.
Finding The Elusive Talent
Converting Internal Talent: The discipline of marketing data science isn’t something that can be learned from a few webinars or a For Dummies book. Success in this field usually requires formal education accompanied by active, on-the-job experience. Still, if you already have some strong analytical talent under your roof it may be possible to convert it to a data science role with some additional investment in training and support. However this will leave you with a hole to fill on your web analytics team, so you are really just trading one challenge for another.
Making the Right Offer: The long and short of things is that strong, proven data science talent is in high demand. The best candidates for marketing data science usually aren’t primarily driven by money. But that doesn’t mean you can expect to find a data guru looking to work below market value out of the kindness of their heart. If you want the best talent, you have to be willing to pay for it.
Do a lot of research on the going rate for data science roles in your location/industry and consult a data scientist recruiter to get a good idea of what constitutes a competitive offer.
Generating Brand Magnetism: Why would a highly sought after expert with their pick of many innovative, exciting and engaging employers settle on you? A strong employment brand is helpful for any organization; having one that’s attractive to top analytics and data science talent is invaluable right now. What can you do to show top talent that your workplace is an environment full of compelling projects, innovative work, bright people and career potential?
Data Scientist Recruiters, Consultants and Contractors: If your internal recruiting team is struggling to locate the marketing data scientist you need, consider partnering with a dedicated data scientist recruiter with a strong talent network and experience attracting top data talent. Or if your marketing situation doesn’t call for a full-time data scientist hire, look into getting temporary access to that talent through a top marketing staffing firm.
