SBIR Phase I:Matching Algorithms and Talent Acquisition System to Improve Start-Up Staffing

Award Information
National Science Foundation
Award Year:
Phase I
Agency Tracking Number:
Solicitation Year:
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Small Business Information
1934 Old Gallows Road, Suite 350, Vienna, VA, 22182
Hubzone Owned:
Minority Owned:
Woman Owned:
Principal Investigator:
Stephen Roberson
(703) 585-1199
Business Contact:
Stephen Roberson
(703) 585-1199
Research Institution:
This Small Business Innovation Research (SBIR) Phase I project aims to create core algorithms for a Talent Acquisition System to programmatically match candidate resumes to startup job opportunities. Startup hiring needs are unique, and the market lacks an effective platform to accelerate and improve this core competency for company building. Generic search of a resume database does not sufficiently capture the unique fit requirements of startup employment nor return acceptable results. This research aims to incorporate (a) limited employer input of search criteria using a simple interface with (b) a broad range of normalized inputs, each individually scored for startup fit, to create a self-tuning algorithm for the search, discovery, and pairing of candidates to the unique needs of startups. The innovation in this approach is to create a system inherently weighted to both the hard and soft attributes of startup work/life. If successful, this effort will remove much of the guesswork by pointing employers to those most likely to excel in these opportunities. Data extraction, scoring techniques, and Bayesian filtering will be applied to resumes, questionnaires, job search histories, social networking maps, candidate referrals, and search terms to feed the algorithm. The broader impact of this project will be to improve the success rate for young companies by accelerating and improving the staffing of strong teams at every level in the organization. The company believes there is significant commercial potential for a startup centric career resource in the U.S. online recruitment industry. Competitive approaches treat startup recruiting as identical to large company recruiting, yet experience indicates there is tremendous demand for an approach built around the unique needs of this community. Companies benefit by (a) focusing on talent which self-selects into this ecosystem and (b) algorithmically filtering these candidates using startup-specific success criteria. This research will create the first platform of its kind specific to startups, something employers have repeatedly requested. The proposed system will deliver both quality and speed biased to the needs of emerging growth companies. It will also provide important metrics on startup job creation which form the best available proxy for private company growth. Service providers in the startup ecosystem will pay for data identifying fast growing companies, and this creates an additional revenue opportunity.

* information listed above is at the time of submission.

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