1. Another Data Science Program? Really
Luke Jankovic – VP Higher Ed, Emsi
Yustina Saleh– SVP Analytics, Emsi
Who here uses or is interested in using labor market data in their group?
Who here knows Emsi or has worked with Emsi in the past?

2. Why? Aligned Economic Ecosystems
People
Higher Ed
Businesses

3. Data Science Skills Clusters - National
Data science comes in many flavors/concentrations. While most data scientists will need to have familiarity with a few of the areas above (software apps, analytics, business intelligence, statistical modeling, big data, scripting), the doses of the concentrations will vary by industry sector, region, even seniority. The distance between clusters show the similarity or overlap between the two.
The vertical axis shows the correlation between the skill and the cluster, the larger the weight the more important the skill is in explaining the trends in the cluster. So Digital Marketing was more prominent in the Analytics cluster than mathematical optimization, although both are statistically significant in the analytics cluster.
The horizontal axis shows the skill frequency. Mathematical optimization appeared almost as many times as Analytics. But the model doesn’t look at frequency alone, but rather how skills coalesce together, making this type of analysis a lot more useful for program design.
The most critical skills shaping the analytics cluster included: Search Engine Optimization, Digital Marketing, Web Analytics, Marketing, Marketing Automation and Market Intelligence. These were not necessarily the most frequent skills, but they coalesced together more, meaning these are important elements to cover in a business analytics curriculum.

4. Data Science Skills Clusters - NYC
Text Mining
Data science comes in many flavors/concentrations. While most data scientists will need to have familiarity with a few of the areas above (software apps, analytics, business intelligence, statistical modeling, big data, scripting), the doses of the concentrations will vary by industry sector, region, even seniority. The distance between clusters show the similarity or overlap between the two.
The vertical axis shows the correlation between the skill and the cluster, the larger the weight the more important the skill is in explaining the trends in the cluster. So Digital Marketing was more prominent in the Analytics cluster than mathematical optimization, although both are statistically significant in the analytics cluster.
The horizontal axis shows the skill frequency. Mathematical optimization appeared almost as many times as Analytics. But the model doesn’t look at frequency alone, but rather how skills coalesce together, making this type of analysis a lot more useful for program design.
The most critical skills shaping the analytics cluster included: Search Engine Optimization, Digital Marketing, Web Analytics, Marketing, Marketing Automation and Market Intelligence. These were not necessarily the most frequent skills, but they coalesced together more, meaning these are important elements to cover in a business analytics curriculum.

5. Note how Amazon has the top share, and note the financial services and social media companies.

6. Data Science Skills Clusters - DC
Data science comes in many flavors/concentrations. While most data scientists will need to have familiarity with a few of the areas above (software apps, analytics, business intelligence, statistical modeling, big data, scripting), the doses of the concentrations will vary by industry sector, region, even seniority. The distance between clusters show the similarity or overlap between the two.
The vertical axis shows the correlation between the skill and the cluster, the larger the weight the more important the skill is in explaining the trends in the cluster. So Digital Marketing was more prominent in the Analytics cluster than mathematical optimization, although both are statistically significant in the analytics cluster.
The horizontal axis shows the skill frequency. Mathematical optimization appeared almost as many times as Analytics. But the model doesn’t look at frequency alone, but rather how skills coalesce together, making this type of analysis a lot more useful for program design.
The most critical skills shaping the analytics cluster included: Search Engine Optimization, Digital Marketing, Web Analytics, Marketing, Marketing Automation and Market Intelligence. These were not necessarily the most frequent skills, but they coalesced together more, meaning these are important elements to cover in a business analytics curriculum.

7. Data science comes in many flavors/concentrations
Data science comes in many flavors/concentrations. While most data scientists will need to have familiarity with a few of the areas above (software apps, analytics, business intelligence, statistical modeling, big data, scripting), the doses of the concentrations will vary by industry sector, region, even seniority. The distance between clusters show the similarity or overlap between the two.
The vertical axis shows the correlation between the skill and the cluster, the larger the weight the more important the skill is in explaining the trends in the cluster. So Digital Marketing was more prominent in the Analytics cluster than mathematical optimization, although both are statistically significant in the analytics cluster.
The horizontal axis shows the skill frequency. Mathematical optimization appeared almost as many times as Analytics. But the model doesn’t look at frequency alone, but rather how skills coalesce together, making this type of analysis a lot more useful for program design.
The most critical skills shaping the analytics cluster included: Search Engine Optimization, Digital Marketing, Web Analytics, Marketing, Marketing Automation and Market Intelligence. These were not necessarily the most frequent skills, but they coalesced together more, meaning these are important elements to cover in a business analytics curriculum.

8. Data Science Skills Clusters – Equipment Manufacturing
Data science comes in many flavors/concentrations. While most data scientists will need to have familiarity with a few of the areas above (software apps, analytics, business intelligence, statistical modeling, big data, scripting), the doses of the concentrations will vary by industry sector, region, even seniority. The distance between clusters show the similarity or overlap between the two.
The vertical axis shows the correlation between the skill and the cluster, the larger the weight the more important the skill is in explaining the trends in the cluster. So Digital Marketing was more prominent in the Analytics cluster than mathematical optimization, although both are statistically significant in the analytics cluster.
The horizontal axis shows the skill frequency. Mathematical optimization appeared almost as many times as Analytics. But the model doesn’t look at frequency alone, but rather how skills coalesce together, making this type of analysis a lot more useful for program design.
The most critical skills shaping the analytics cluster included: Search Engine Optimization, Digital Marketing, Web Analytics, Marketing, Marketing Automation and Market Intelligence. These were not necessarily the most frequent skills, but they coalesced together more, meaning these are important elements to cover in a business analytics curriculum.

10. Data Science Skills Clusters - Biotech
Data science comes in many flavors/concentrations. While most data scientists will need to have familiarity with a few of the areas above (software apps, analytics, business intelligence, statistical modeling, big data, scripting), the doses of the concentrations will vary by industry sector, region, even seniority. The distance between clusters show the similarity or overlap between the two.
The vertical axis shows the correlation between the skill and the cluster, the larger the weight the more important the skill is in explaining the trends in the cluster. So Digital Marketing was more prominent in the Analytics cluster than mathematical optimization, although both are statistically significant in the analytics cluster.
The horizontal axis shows the skill frequency. Mathematical optimization appeared almost as many times as Analytics. But the model doesn’t look at frequency alone, but rather how skills coalesce together, making this type of analysis a lot more useful for program design.
The most critical skills shaping the analytics cluster included: Search Engine Optimization, Digital Marketing, Web Analytics, Marketing, Marketing Automation and Market Intelligence. These were not necessarily the most frequent skills, but they coalesced together more, meaning these are important elements to cover in a business analytics curriculum.

12. It’s about finding your niche!
While there are core data science skills that are similar across regions and industries, the variations we have seen could industries present in their regions were stark.
Higher ed institutions no doubt need to be equipping students with a core foundation of data science skills, but they must understand the market they are serving, too.
Eastern Washington University, four hours east of Seattle, is doing this with its partnership with Microsoft. It found a way to stand out in a sea of data science and analytics programs and partner with a world-renowned company in its home state.
True, not all data science graduates will stay in the region (or state) where they went to school. But many institutions, like Eastern Washington, actively pursue industry partnerships and sponsorships. Doing this allows colleges and universities to develop a niche in the data science education market and keep a pulse on industry needs.
Otherwise they’ll be just another data science program.
Data science comes in many flavors/concentrations. While most data scientists will need to have familiarity with a few of the areas above (software apps, analytics, business intelligence, statistical modeling, big data, scripting), the doses of the concentrations will vary by industry sector, region, even seniority. The distance between clusters show the similarity or overlap between the two.
The vertical axis shows the correlation between the skill and the cluster, the larger the weight the more important the skill is in explaining the trends in the cluster. So Digital Marketing was more prominent in the Analytics cluster than mathematical optimization, although both are statistically significant in the analytics cluster.
The horizontal axis shows the skill frequency. Mathematical optimization appeared almost as many times as Analytics. But the model doesn’t look at frequency alone, but rather how skills coalesce together, making this type of analysis a lot more useful for program design.
The most critical skills shaping the analytics cluster included: Search Engine Optimization, Digital Marketing, Web Analytics, Marketing, Marketing Automation and Market Intelligence. These were not necessarily the most frequent skills, but they coalesced together more, meaning these are important elements to cover in a business analytics curriculum.

13. Questions Luke Jankovic 208-596-5332 Luke@economicmodeling.com
Yustina Saleh