Mercy College / Executive Director, Institutional Research, Evaluation, Analytics

  • September 20, 2016 10:51 AM
    Message # 4264908

    Mercy College is seeking an Executive Director of Institutional Research, Evaluation and Analytics.  This newly created position is responsible for driving the institution’s vision for and building capacity to enhance a business intelligence and reporting environment.  For more information and to apply, please visit:

  • May 31, 2017 12:59 PM
    Reply # 4863172 on 4264908

    I am a collaborative engineering professional with substantial experience designing and executing solutions for complex business problems involving large scale data warehousing, real-time analytics based on Natural Language Processing (NLP), and reporting solutions based on intuitive architecture that effectively analyze and process petabytes of structured and unstructured data. I have an extensive background in architecting and developing large-scale data processing systems and serving as a subject matter expert in data warehousing solutions while working with a variety of database, analytical, and statistical based technologies. This experience in architecting highly scalable, distributed systems using different open source and specific vendor tools as well as designing and optimizing large, multi-petabytes of clustered data warehouses were primarily in the clinical/ medical research, academia, computer integrated manufacturing, military battlefield self-awareness systems, aerospace, and financial/investment systems. Based on this experience I was able to integrate state-of-the-art Big Data technologies from IBM and Oracle into the overall architecture and lead a multi-team of Senior Data Scientists, Software Engineers, and Enterprise Architects through the design, development, engineering testing, and implementation phases. I have been working in industry and academia with Analytics and Artificial Intelligence in designing and constructing neural networks to be used as computational models in machine learning based on NLP and linguistics. These models were used as the basis to support the execution of statistical applications developed in R and SAS languages, and algorithms based on discreet and continuous mathematics and inter-operability with rule-based application languages. I have used NLP as a means to examine and analyze patterns of data, statistics, and related content relative to their behaviors predicated on metamorphosis processes as well as to the next level which is providing human intelligence with a secondary self-awareness that is technology generated and in support of the primary self-awareness which is human intelligence. In summary, this means that as data and related content changes due to interactions with applications, human interactions, and streams of research, the use of these NLP applications become self-aware of these new patterns through interpretative learning. Based on this self-awareness information is derived that allows actions and recommendations to be readily added to these patterns and the extension of these patterns across other patterns by predictive and inferential models. The net result is that what we learn on a day-to-day basis by interacting with data, statistics, and content is exponentially and organically increased but the relevancy from this is meaningful information that works for us, for example, the ability to give back to us the missing chemical component or surgical technique for DNA molecular cell structure breakdown in order to address a specific cause to autism, or increase business competitiveness in your specific marketplace by niche. The application of NLP was the missing link to the work completed in Analytics.

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