Looking for a data science job that will let you express your creative side?
Here are some cool ideas on where you might be able to find one…
6 – High Rollers (Casino Management)
Math! Risk! Marketing! There’s more to Vegas than just the blackjack tables. (Although the MIT crew cleaned them out pretty good). The gaming industry is a heavy user of analytics – not just at the actual gaming tables, but in the meta-games of marketing strategy, fraud detection, and facility / experience development. Data drives every aspect of the business.
Casino marketing is a fast paced game of using data to understand gambler psychology and design experiences which appeal to the right customers. Sometimes the best strategies can be counter-intuitive – remember that other casinos are competing for a similar audience, offering similar incentives and games. Your goal is find unique ways for the casino to connect with your audience and win their loyalty. You’re constantly mapping trade-offs between promotional incentives, marketing cost, game pricing, and playing time.
This industry is also on the cutting edge of fraud detection technology and security management, due to the tremendous potential for cheating and other misbehavior. Everything on the gaming floor is monitored and automated systems help casino staff identify when a guest is up to no good.
5 – Food and Wine Analyst
Stand back, the robots are in the house. A team of data scientists at IBM has already started working on a system which uses data to develop new and interesting recipes. Other new data science jobs are focused on related problems such as food processing, food packaging, and cold chain logistics. We’re designing new ways to move food from farm to table, so the final product is fresher, safer, and easier to prepare.
The problems range from understanding diner preferences to analyzing supply chain performance. Imagine getting food to market faster and with less spoilage along the way. Deep analysis of wine and beer preferences can help identify consumer preferences and link them back to the right ingredients and growing conditions. Similarly, data can be used to craft a deeper understanding of consumer tastes and creatively remix familiar recipes with new ingredients. Anyone want a lamb and feta burrito, blending the gyro and the burrito? (they’re delicious)….
And like any creative cooking occupation, you occasionally have the option of personally presenting your creations to the adoring public…
4 – Music and Film Analytics
What if we could predict if a song or movie has a good chance of being successful before we release it? Or better yet, identifying which segments of the audience would appreciate it most? What if we could “tweak” art a little bit, to make it more appealing to the masses?
The future is now. Using advanced data on consumer preferences and viewing habits, analysts have built advanced models which give insights into audience preferences. These data science jobs are focused on building models that consume all sorts of data, ranging from statistical analysis of art and music patterns to audience response information from sources such as you-tube and streaming tube sites.
3 – Search Quality
Search engines guide our lives today, ranging from web search (Google) to product recommendations (Amazon and E-commerce) and knowledge management systems. A good search engine understands how to divine user intent from similar queries – for example, when I type sushi into my browser, am I looking for a restaurant (local, of course), instructions on how make it, or guide to the history of sushi? Incorporate the fact that a full 15% of the queries Google handles are unique (never seen, never repeated) and the problem gets harder.
But success can be measured – in the form of user satisfaction. What % of the audience clicks on a result – and stays there? The goal is to satisfy the searcher’s intent by guiding them to the right answer. This can be measured, using both click tracking and user surveys. The quest to deliver the most relevant possible results gets into document mining, topic/sentiment analysis, and machine learning experiments to use user response data to fine tune the results.
Search Quality also protects the general population from the dark side of the force – black hat web spam and recommendation fraud. As an increasing share of human attention is funneled through search engine technology, there is a temptation to manipulate the results to push sites and products up the ranking system. Recommendations can be faked. Search ranking signals can be manipulated. Social networks can be spammed with junk endorsements. Careful analysis and fraud detection algorithms can be used to find and block these disruptions.
2 – Info-graphics Specialist
No matter how good an idea is, it does not have value unless it can be effectively communicated to an audience. Enter the info-graphics expert, tasked with taking data and turning it into a simple, crisp image that can be shared with the general public. Part statistics, part art, this is a critical part of bringing the data science cloud back down to earth.
Good design skills are essential, along with a good grasp of data science and communications.
1 – Digital Marketing / Web Publishing
Emerging from the direct and database marketing community in the nineties, digital marketing embraced data science right from the start. The entire industry is a massive data science problem, focused on efficiently connecting merchants and customers. Every piece of the marketing process can be tested and proven, using data. Which banner? What message? Which subsets of the audience? Will a visitor buy right now or can we persuade them to sign up for a series of emails that will demonstrate why they need our product?
On the corporate side of things, you help design promotions and events and measure their effectiveness. You can research consumer preferences. For those who want to go the James Bond route, you can analyze competitor campaigns to figure out what they learned. Everything is woven together in a mathematical tapestry which describes how you connect customers and products.
Unlike many of the other industries we’ve profiled, this is space where you can literally create your own job. Pick a product you like, pick a target audience. Start thinking about how you can connect them together, using everything from inbound marketing (create compelling content and position it to generate interest on social media / search engines) to paid banner advertising campaigns. Then go build a website to promote your offer.
The best way to get started down these paths is to reach out and connect with folks already working in these fields. Find meetups and conferences – most have some kind of social hour you can use to meet people. See if anyone is hiring interns.
With a little hustle, you can find a job that combines data science with a little creative flair!