NICHOLAS E. BOWMAN

*** ********* *****, *******, ** 18458 773-***-****

ac2zvc@r.postjobfree.com http://www.linkedin.com/in/nicholas-ernest-bowman PROFILE

Data scientist with a background in neuroscience and experience in predictive analytics, natural language processing, deep-learning and big data platforms. Passionate about communicating actionable insights through compelling visualization of diverse unstructured data. RELEVANT EXPERIENCE

Data Scientist: Cognitive Genomics (remote) November 2016-Present Data-mining of millions of scientific studies that pertain to the products Cognitive Genomics offers. Utilizing cutting- edge text-mining tools to search for genetic mutations that relate to cognitive function and extracting the relevant information to produce customized reports. Creating complex models for predicting cognitive phenotypes and developing comprehensive tailored advice for customers based on their genotypes. Data Scientist - Consultant: CNA (Chicago) July 2014-November 2016 Created a predictive model for detecting recovery (subrogation) opportunities for Worker’s Compensation claims. Used natural-language processing to analyze claim diaries, which supplemented the use of various structured data. Developed spell-correction and abbreviation-disambiguation tools and other in-house algorithms for cleaning and structuring textual data. Continued to enhance the TBI model (see below) to include a self-generating report that notifies specialists to investigate, collects feedback on actions taken, and helps monitor the financial impact of the intervention.

Data Scientist - Post-Doc: CNA (Chicago) June 2014-September 2014 Designed a model that predicted which motor-vehicle-accident claims involving head injuries were likely to result in an allegation of Traumatic Brain Injury (TBI). Developed text-mining algorithms for broader use within the company, which were used by a number of different teams to augment their models. Research Associate: Northwestern University (Chicago) September 2007-June 2014 Devised novel experimental paradigms and data-analysis methods, leading to the first evidence demonstrating how and where the human brain accumulates information to facilitate ambiguous decisions. (See publication information below.) Developed computational models of decision-making behavior and its neural correlates. Mentored PhD students on projects that demonstrated how confidence evolves during a decision, using psychophysical tools and Bayesian decision theory.

TECHNICAL SKILLS

Software and Programming Languages: R, Python, SQL, SAS, Oracle, Hadoop (Spark, Hive, Pig, Impala), Tableau Statistical Methods: Time-series analysis, regression models, principal component analysis Machine Learning: Deep-learning, classification, regression, clustering, random forests, Naïve-Bayes EDUCATION

Northwestern University September 2007-June 2014

Doctor of Philosophy in Neuroscience (focus on perceptual decision-making) University of Chicago September 2001-June 2005

Bachelor of Arts in Biological Sciences (specialization in Neuroscience) ACADEMIC HONORS AND AWARDS

NIH Training Grant (2011-2013): awarded to select PhD students in the Department of Neuroscience at Northwestern University SELECTED PUBLICATION

Nicholas E. Bowman, Konrad P. Kording, Jay A. Gottfried (2012). Temporal Integration of Olfactory Perceptual Evidence in Human Orbitofrontal Cortex. Neuron (pp. 916–927)

OTHER

Coursera Courses: Specialization in Data Science (10 courses); Specialization in Deep-Learning (3 of 5 courses – waiting on the last two) International: Secondary education in England; dual-citizenship (British and American) Languages: English (native), German (basic), Spanish (basic) Volunteering: Greenhill (outdoor sports instructor - Northern Ireland: 1999-2000), Good Neighbors (homeless outreach - Chicago) Interests: Tennis, volleyball, biking, flash fiction, chess, culinary adventures, and the great outdoors