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Data scientists are hot commodities these days. Although just 0.2% of US companies employ single data scientists, starting salaries in the field topped $200,000 last year. By 2018, McKinsey predicts a 50-60% shortfall between demand for data scientists' deep analytic skills and the extant supply.

Things don't get much better on data scientists' home turf. Although Big Data is a huge buzzword in the information technology and services sector, just 0.3% of those companies employ a data scientist.

If your marketing team is searching for its first data scientist, it's hardly alone.

Where are the data scientists?

Part of the reason many marketers are having difficulty finding data scientists is because they're looking in the wrong places.

Unlike many from the business world, most data scientists aren't trawling company job boards. Many are academics by trade—particularly in fields like mathematics, engineering, and computer science—and must be coaxed out by corporate recruiters. For example, Yelp's Chris Farrell was drawn to the business world after completing a Ph.D. in astrophysics and spending years parsing data from a particle accelerator.

Much like Farrell, I began in the applied sciences. Although I now work as Jumpshot's vice-president of data science, I'm an engineer by training. I earned two bachelor's degrees from University of California-Berkeley (one in material science engineering and one in mechanical engineering) and a bachelor's degree in economics from University of California-Santa Cruz. I'm a marketer now, but I sure didn't plan to be during my college years.

How can data scientists help marketers?

When data scientists like myself transition into the business world, we're looking to contribute to engaging, cutting-edge projects.

Marketing departments, in particular, offer exciting chances to work with Big Data during a period of industry-wide innovation. Though marketing has traditionally been very qualitative, we're teetering on the edge of its transition to a science.

Traditional marketers will always have their place—graphics need designing, blog posts need writing, and social media needs managing—but marketing is rapidly becoming a field of numbers rather than letters.

Individualized marketing, in particular, has become a departmental priority for nine out of 10 marketers, according to Teradata's 2015 global data-driven marketing survey. This approach treats each and every customer as an individual marketing opportunity, and it requires data on each person's preferences, search history, and buying habits. It's a big reason 78% of surveyed marketers now say they use data systematically, compared to just 36% in 2013.

To successfully manage the data, 84% of those surveyed see a need for greater strategic partnerships between IT professionals and marketing departments.

How can collaboration occur between data scientists and marketers?

Although marketing today is changing rapidly from art to science, the challenge is no longer gathering the data. Each day, we collectively create 2.5 quintillion bytes of data, and 90% of the world's data has been created in just the past two years.

Today, a marketer's challenge is to effectively analyze that data to glean customer insights and use it to craft compelling stories. To that end, marketers and data scientists must collaborate. But most marketers aren't accustomed to a data scientist in the department, and the chasm between their two worlds can cause marketers and data scientists to silo themselves off from one another.

At Jumpshot, we use these tactics to foster collaboration between our two halves:

1. Communication in a common language

Data scientists may be used to speaking in terms of chi-squared values and confidence intervals, but their messages get lost on their teams without a little interpretation. Other members of Jumpshot's data team and I always present our findings without using mathematical terms of more than three charts or tables.

2. Teamwork through collaborative projects

Once your marketing department has hired a data scientist, the worst move you can make is to separate him from the rest of the team with all-day number crunching. Find collaborative projects to help the data scientist become acquainted with the rest of the team in an organic way. Beautiful information graphics, interactive online data maps, and statistically accurate whitepapers all provide opportunities for teamwork to develop through collaboration.

3. Camaraderie with brown-bag lunches

Although marketers and data scientists have very different backgrounds, they're really two essential parts of the same team. But to work together, both have to understand the others’ strengths and concerns. At Jumpshot, we orchestrate weekly informal brown-bag lunches, where marketers and data scientists can share ideas in a low-stakes environment. A data scientist needs an understanding of marketing strategies behind each campaign to know why he or she is collecting and analyzing data, and a marketer should be able to answer basic questions about sample sizes and confidence intervals to curious clients or customers.

When professionals from two different worlds collide, the transition can be difficult. Marketers can feel threatened by terms and data they don't understand, and data scientists can feel uncomfortable at the uncertainty and imprecision of the business world. But together, marketers and data scientists can create campaigns that are artful, scientific, and more individualized than ever.

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ABOUT THE AUTHOR
image of Hong Tsui

Hong Tsui is vice-president of data science at Jumpshot, a San Francisco-based startup that offers marketing analytics for travel, retail, and media companies.

LinkedIn: Hong Tsui