Headquartered in New York City, with decades of experience in technology, financial services and recruitment, our team has been immersed in research and development of robust unstructured text data mining solutions built upon our proprietary “Weighted Topic Scoring” and “Domain-Specific Language Processing” methodologies, which work as an alternative or adjunct to Natural Language Processing. We have been awarded three U.S. Patents in “Profile Matching of Unstructured Data” and “An Engineering Approach to NLP.”
Janet Dwyer, CEO/Founder
Janet has 15 years of combined experience in software product development, I.T. recruitment and account management, with a focus on Wall Street’s financial services firms, the Fortune 1000 and other hi-tech companies. Prior to her current roles, she was a Partner in a NYC startup I.T. staffing firm and District Manager in a boutique I.T. consulting firm specializing in derivatives and capital markets I.T. staffing.
John Harney, CTO/Founder
John is the technical creator of DataScava and TalentBrowser, using his expertise in Visual Studio, SQL Server, cloud computing and full life cycle software development, including 20+ years of experience in software architecture, project management and development. His career began in Ireland, where he created financial decision support software for Fixed Income/FX/short-term cash markets, providing software to 19 of 23 banks in Dublin.
Al Mellina, Strategic Advisor and Board Member
Al is former CEO/Managing Partner at Gartland & Mellina Group (GMG), a Management Consulting company that serves the Financial Services industry with locations in New York City, London and Toronto, acquired by Sia Partners in 2019. Their practices include Wealth Management, Capital Markets, Compliance, Strategy and Solutions, and Asset Recovery. Prior to GMG, Al was a Partner in BearingPoint and KPMG for over 11 years. He earned his BS in Physics and MBA in Marketing from Iona College.
Scott Spangler, Senior Data Scientist, Principal Consultant
Scott is a named IBM Distinguished Engineer, former IBM Watson Health Researcher, Chief Data Scientist, and the author of the book “Mining the Talk: Unlocking the Business Value in Unstructured Information.” He has over twenty years of experience designing and building solutions for unstructured data, and over ten years focusing specifically life sciences and drug discovery. Scott is skilled at leading small teams to apply advanced machine learning and cognitive computing techniques to solve discovery problems involving heterogeneous data sets. He excels at communicating effectively with principal investigators in life sciences, executive stakeholders, software engineers and end users. Areas of specialty include Unstructured Text Analytics for Scientific Discovery, Data Analysis, Statistics, Design of Experiments, Java Application Development, Intellectual Property Analysis, Corporate Brand Reputation Analysis.