James Decker

About James Decker

Primary Goal: Enabling businesses and non-profit organizations to acquire knowledge through data and make efficient data-based decisions. General Skills: Recommending, designing, and implementing data science systems and models. Managing complex knowledge-based systems that return value to organizations. Designing, implementing, and validating statistical and knowledge-based analyses and software systems for competitive advantage. Experience Summary: 30+ years developing software systems and tools for analyzing human data (clinical health, attitude, sensory, opinion, and consumer-behavioral) data with advanced methods (e.g, Regression models, Structural Equation Models, Bayesian belief networks, Item Response Theory, preference maps). 25+ years developing quantitative systems in research environments. People & project management in these contexts. Broad,cross-discipline education (Psychology, Computer Science). Extensive work-with-experts-in-field experience. Highly developed communications skills and experience making in-depth presentations of results. Specialties: Text Analytics, Predictive data modeling, Segmentation, Psychometrics, Quantitative analysis, Regulatory compliance, Statistical system building. Analytic/Scientific software architecture & design. System Validation and Unit-Testing. Extensive use of specialized knowledge-based software for text-mining and advanced machine learning. Primary application areas : Consumer and employee understanding (human motivation), consumer sensory research, Clinical research, Analysis of medical record and insurance data. Additional Keywords: Data Science, Business intelligence, Machine Learning, Text analytics, Measurement theory, Cognitive theory, Sensory theory, Validation. Primary Software tools SAS, SPSS, R, BayesiaLab, LISREL, Python, PolyAnalyst. Other specialized languages & platforms.

Experience

1. Data Scientist Natural Language Processing

   Apixio

   Sep 2020 — Present · WFH - Cincinnati, OH, US

   Development of NLP Clinical Record Analysis Engine global and client-specialized product capabilities. Apixio\'s (formerly SyTrue) NLP system is used internally for analysis of unstructured clinical medical record data and is also licensed by external clients. The engine uses specialized rules, standardized code libraries (e.g. SNOMED, RXNORM, LOINC), NLP methods, and machine learning processes to extract information of value from unstructured (typically scanned) clinical medical record data. SyTrue, Inc, formerly a software product company that originally developed the Apixio NLP engine was acquired by ClaimLogiq, Inc, summer, 2022. ClaimLogiq merged with Apixio in June, 2023. My role as a Data Scientist started with SyTrue, Inc.

Education

• Grinnell College

  BA, Psychology / Philosophy

  1971 — 1975

• Indiana University Bloomington

  M.A. (with thesis), Cognitive Psychology

  1975 — 1977

• University of Illinois Urbana-Champaign

  PhD Program Sans Thesis, Computer Science - Artificial Intelligence / Machine Learning

  1982 — 1985

• University of Minnesota

  Economics, Finance, Math. Courses

  1979 — 1980

• Marietta Senior High School

  High School, Scientific/Academic

  1966 — 1970