{"id":8647,"date":"2019-02-22T10:49:11","date_gmt":"2019-02-22T15:49:11","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/kaggle-and-the-democratization-of-data-science\/"},"modified":"2019-02-24T03:10:12","modified_gmt":"2019-02-24T08:10:12","slug":"kaggle-building-a-market-for-data-science-and-scientists","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/kaggle-building-a-market-for-data-science-and-scientists\/","title":{"rendered":"Kaggle: Building a Market for Data Science (and Scientists)"},"content":{"rendered":"

The online data science and machine learning community Kaggle<\/a> is just one of the many two-sided platforms that have emerged in recent years. Recently acquired by Google<\/a>, the site is home to over one million users<\/a> ranging from computer science Ph.D. holders conducting cutting edge research to absolute beginners. Kaggle is best known for its data science competitions that offer (substantial) cash prizes, but it also serves as an educational tool for autodidacts as well as a place to present one\u2019s portfolio of related work.<\/p>\n

Various organizations use Kaggle to sponsor contests to develop machine learning algorithms for a slew of purposes. The analytics company Two Sigma<\/a> recently created a competition to build an algorithm predicting stock market fluctuations in relation to news developments, offering $100,000 in total prize money<\/a>. The United States Department of Homeland Security sponsored a challenge with a first-place prize of $500,000<\/a> for the algorithm that best streamlines airport passenger screening procedures.<\/p>\n

Value creation<\/strong><\/p>\n

By allowing organizations to crowd-source answers<\/a> to extremely complex questions, Kaggle serves as a marketplace for these solutions. For what is usually less than the cost of a single full-time data scientist (almost always $100,000 or more a year<\/a>), companies can employ an army of freelancers to build bespoke models for their problems. Furthermore, it allows companies to conduct a completely merit-based evaluation<\/a> of potential employees. Applicants (who may or may not know they are trying out for a full-time position) also have the chance to earn money while going through the recruiting process for a position with the hosting company.<\/p>\n

Although the strongest attractions for users are the competitions, the educational and portfolio aspects of the site serve as a mechanism to draw data scientists to it and keep them there. The ability to explore other users\u2019 algorithms and collaborate on problems has almost certainly led to the massive growth in the platform\u2019s user base.<\/p>\n

Finally, Kaggle creates value for society by organizing competitions on a pro bono<\/em> basis<\/a> for non-profit and research organizations. By partnering with these groups to facilitate research into important but less financially lucrative problems, Kaggle helps direct the brainpower of its user base towards noble ends.<\/p>\n

Value capture<\/strong><\/p>\n

It does not appear that Google captures substantial monetary value from Kaggle. The platform does not run any advertisements and signing up is free for users. Organizations hosting competitions, however, likely pay a fee<\/a> to do so, and Kaggle may offer consulting services<\/a> to help the organization structure its competition. Press observers have speculated<\/a> that the primary reason Google made the acquisition is to improve its brand in the data science community and to facilitate recruitment of these in-demand professionals. Kaggle\u2019s parent company likely pays close attention to the top-ranked contestants on the platform, putting them in touch with Google\u2019s recruiting team as appropriate.<\/p>\n

Conclusion<\/strong>\u00a0<\/strong><\/p>\n

By connecting talented data scientists with tough problems, motivating them through lucrative cash prizes, and assisting their professional development through educational and portfolio resources, Kaggle creates substantial value for its users. Partner organizations can similarly develop custom-built solutions for their business challenges while identifying the best talent to recruit. Finally, Google earns revenue from these partners while at the same time building its credibility in the arena of data science. The mutual value creation for all of the involved parties suggests that Kaggle will remain a dominant player in the space for years to come.<\/p>\n

 <\/p>\n

Image from Kaggle<\/a>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Kaggle is an innovative two-sided platform that connects companies facing hard problems with the data scientists who can solve them.<\/p>\n","protected":false},"author":10187,"featured_media":8649,"comment_status":"open","ping_status":"closed","template":"","categories":[134,1265,2382,366],"class_list":["post-8647","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-analytics","category-data-science","category-innovative-platforms","category-machine-learning","hck-taxonomy-organization-kaggle","hck-taxonomy-industry-computer","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/dig-it-blog-post-assignment-i-innovative-platforms\/","yoast_head":"\nKaggle: Building a Market for Data Science (and Scientists) - Digital Innovation and Transformation<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/kaggle-building-a-market-for-data-science-and-scientists\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Kaggle: Building a Market for Data Science (and Scientists) - 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