Brady Hoskins
I am an avid believer in the power of data and enjoy working with data to solve problems that help others. I previously completed my Master of Science - MS in Applied and Computational Mathematics and Statistics: Data Science Specialization from the University of Notre Dame. I also participated in several machine and deep learning research projects during a two year undergraduate fellowship for the Department of Psychiatry at the University of Iowa. I am currently working as a Data Scientist at Principal Financial Group.
Skills
- Machine learning and deep learning
- Databases, SQL, Neo4j
- Image recognition and computer vision
- Nautral langauage processing
- Statistical Analysis, SAS
- Data visualization
- Storytelling
- Object-oriented programming (OOP)
- Algorithms
- Software Engineering
Experience
Data Scientist II
Partnered with language AI team on comprehensive customer initiative using data modeling to aid customer journey understanding to enhance customer ease of doing business. Appointed as lead data scientist for data and tooling requirements while creating roles and environments for enterprise wide AWS customer and marketing analytics R&D accounts. Managed and mentored an analytics intern through 2 projects utilizing PowerBI dashboards. Served as subject matter expert for getting 10 team members acclimated to AWS during our transition to the cloud. Performed analysis and natural language processing on customer survey, free response, and call transcript data to derive quarterly insights and determine key drivers for business stakeholders to enhance customer experience. Worked on 14 additional descriptive and prescriptive analytics projects delivering results to key stakeholders.
Software Engineer I
Engineered 15 new Salesforce functionalities using Java, Javascript, and HTML5 to enhance speed and capability of our business unit members. Enacted 1-10 daily SQL database changes to fix errors and adjust the business unit’s data tables.
Health Services Officer
Supervise the establishment of platoon operations, direct setup operations and supervise the displacement of treatment squads/teams with company headquarters and supported units.
Machine Learning Research Assistant
Developed machine and deep learning models on 5 projects to find patterns in genetic and image data linked to Autism Spectrum Disorder. Contributed to research that resulted in two publications in the field of biomedical imaging.
Software Engineer Intern
Engineered with Java, JavaScript, and IBM Process Designer to make improvements to image workflow processes.
Cyber Security Intern
Participated in research of classified network diagnostic tools.
IT Assistant
Designed iOS applications for field agents. Made design changes to company webpage.
Projects
Below is a various selection of academic and personal projects that I have worked on:
Medical School Residency Research Dashboard
A dashboard I am working on to assist my fiance in her residency application research process.
R Shiny Data Cleaning Data Visualization Dashboards
Modeling Autism Related Missense Variant Protein-Protein Interactions with a Siamese RNN
A first of its kind attempt to model missense variant PPI
Working to gain a greater understanding of mutations in ASD that will lead to better diagnostics.
Python R Deep Learning RNN Data Cleaning
Analyzing Retinal Images to Classify Mental Health Disorders
Attempting to predict mental health disorders by observing degradation of retina
The intent of this project was to search for a quick, early onset identifier for potential mental health disorders.
Python Deep Learning Image Recognition CNN
Predicting Autism Spectrum Disorder (ASD) at Birth Using Machine Learning
Using newborn metabolite data to train machine learning models to detect ASD risk factors
Autism Spectrum Disorder (ASD) diagnosis is often a lengthy, difficult process typically conducted at the ages 2-5. Here the focus was to provide a simple way to detect at risk children at birth.
R Machine Learning Classification
South Bend Civic Data Analysis Shiny App
A dashboard to analyze various datasets focusing on areas of interest to South Bend
R Exploratory Data Analysis Shiny Data Visualization GIS
Identification of Malignant Tumors in Breast Tissue
Utilizing machine learning techniques to assist in identifying malignant tumors
R Machine Learning Exploratory Data Analysis Classification
Education
University of Notre Dame
University of Iowa
University of Iowa
University of Iowa
Certifications
- AWS Certified AI Practioner
- AWS Certified Machine Learning Specialty
- Microsoft Certified Azure AI Fundamentals
- Microsoft Certified Azure Data Scientist Associate
- AWS Cloud Practitioner
- DeepLearning.AI & AWS Generative AI with Large Language Models
Publications & Presentations
-
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)
Material
Event site
Sex Differences in the Brain | Divergent Results from Traditional Machine Learning and Convolutional Networks
-
2019 Adolescent Brain Cognitive Development Neurocognitive Prediction Challenge (ABCD-NP-Challenge 2019)
Material
Event site
Ensemble Modeling of Neurocognitive Performance Using MRI-Derived Brain Structure Volumes
-
Poster session presented at Computational Psychiatry Symposium 2019
Material
Event site
Predicting Autism Spectrum Disorder (ASD) at Birth Using Machine Learning
-
Poster session presented at Spring Undergraduate Research Festival
Material
Event site
Predicting Autism Spectrum Disorder (ASD) at Birth Using Machine Learning
Honors & Awards
- Spot Award for oustanding performance at Principal Financial Group 2020
- Frank A. Park Scholarship for academic achievement in Computer Science 2020
- Iowa Research Center for Undergraduates Research Fellow 2019-2020
- 2nd Place team at ABCD-NP-Challenge 2019