Proposed and developed a POC survival analysis model to provide additional context into nurse turnover.Developed a more robust data preparation and feature engineering workflow showing preliminary improvement in accuracy (3%), and AUC (3%) compared to the production model.Combined our existing model framework with the survival model to improve identification of nurses at-risk for attrition by ~17% in preliminary testing.Wrote SQL queries and Python code to pull additional features and join them with existing data to improve model performance.Created a near-real-time dashboard in using streamlit and plotly to identify trends in patient discharge times across 5 hospitals.Visualized key metrics for each hospital to identify hospital performance baselines and potential bottlenecks in operations.

Support Public Sector customers as a technical advisor for cloud best practices, focusing on machine learning.Presented cloud fundamentals, live whiteboarding for a simulated hospital ETL workload, and created a full demo of this workload over the course of 2 months in 3 mock customer environments. Passed the AWS Solutions Architect Professional Exam during the presentation time frame, over a year ahead of team certification requirements.Created a full working demo to generate simulated hospital emergency room patient monitoring data at scale, by modeling ER bed capacity for hospitals in an average county in California. The architecture then processed the streaming data to evaluate patient health metrics using Amazon SQS and AWS Lambda in near real-time, stored results in Amazon S3, queried them with Amazon Athena and AWS Glue, and then visualized them with a custom dashboard in Amazon QuickSight.Extended our research on kidney cancer progression biomarkers by including clinical outcomes data in our pipeline, comparing our XGBoost results with AutoGluon, and by documenting our project in an academic paper that is currently under review.Our kidney cancer research was accepted into the AMIA Clinical Informatics Conference 2022 in Houston, TX where I will be presenting our research in a poster session on May 25th, 2022.Improving the front-end of an internal tool used to monitor early career talent progression for Solutions Architects supporting Public Sector using TypeScript and React.Skills Developed: automation, object-oriented programming, TypeScript, React, AutoGluon, ETL, front-end development, survival analysis, public speaking, customer interaction, presentation skillsCertifications: AWS Solutions Architect Professional

Led a multi-team project to perform ETL, sentiment analysis, and a custom dashboard of Tech U survey data to gain further insights from resident feedback.Wrote and edited project proposals for creating a data lake for educational programs at AWS, and the survey sentiment analysis project mentioned above.The sentiment analysis project is projected to save 3-5 hours a week of manually reviewing survey responses, creating data visualizations, and interpreting feedback into action items. It will also provide deeper insight into resident feedback over time.Presented our sentiment analysis project to leadership and Amazon at large.Collaborated with data scientists to identify potential biomarkers for kidney cancer progression using ML and bayesian optimization on microRNA, mRNA, and proteomics data.Placed in the top 20% (13th out of 66 participating teams) in an Amazon-wide internal image classification competition using image augmentation, Rekognition, and keras.Peer-mentored a pilot group of non-Tech U residents on presentation skills, big data, and S3.Completed a 6-month virtual training program in AWS fundamentals, doing technical sprints, labs, and presentations on the following topics:- Networking- Highly Available Web Apps- Governance and Compliance- Big Data- IoT and ML- Microservices- End User Computing- Migrations, Hybrid Architecture, and Disaster RecoverySkills Developed: AWS best practices, presentation skills, image augmentation, computer vision, NLP, data visualization, multi-omics analysis, XGBoost, kerasCertifications achieved: AWS Machine Learning Specialty, AWS SysOps Administrator Associate

Linux Systems Administrator for Administrative Solutions Group at BYUManaged over 16 RHEL 7 servers for production and development applications using VMware vSphere and Morpheus.Cut build, test, and deploy time for an important GitLab CI/CD pipeline by nearly 50% by deploying the app to Docker containers.Built an internal wiki for training Systems Administrators on IT best practices around security, networking, backups, basic Linux, Docker, DevOps, and server maintenance.Trained 2 developers and a new system administrator on IT fundamentals.Rebuilt our self-hosted production GitLab server from a complete previous server loss.Developed automated server backup scripts using cron jobs and rsync.Skills developed in role: Linux, automation, DevOps, GitLab, SSL certificate management, security, networking, VMware vSphere, Morpheus, cron, backups, Redhat Enterprise Linux

Flagship cohort for Internships for Good at AWSDelivered professional presentations and collaborated with a national team in a fully remote environment.Developed record matching algorithms in Python using pandas, recordlinkage, jellyfish, boto3, and json packages at scale: Combined datasets, matched, processed, and reformatted 1,000,000+ records in ~2 minutes.Worked with external customers on a data management workload leveraging several AWS services: S3, Glue, Lambda, Elasticsearch Service, Kinesis, API Gateway, EC2, and Cloud9.Created an architecture to enable HIPAA compliance with AWS services.Delivered a working, proof-of-concept demo of the full architecture in three 2-week sprints.Used Glue, S3, and Lambda to define and run a serverless ETL process.Handled streaming data at scale by leveraging Kinesis Data Streams and Firehose to send data to Elasticsearch.Developed a Lambda function in Python to translate HTTP API requests into an Elasticsearch querying format.Completed the 3-day Machine Learning University Accelerated course for Tabular Data.Implemented data pre-processing techniques in sklearn using techniques such as SimpleImputer and OneHotEncoder, using a pipeline to automate those steps.Learned about various ML algorithms, and implemented algorithms such as KNN, Decision Trees, Random Forest, AdaBoost and Neural Networks to perform classification on a large, real-world Amazon dataset.Used hyper parameter tuning methods like GridSearchCV and RandomizedSearchCV to find the optimal hyper parameter combinations for the models above.Skills developed: AWS best practices, presentation skills, record linkage, data deduplication, machine learning, ETL fundamentalsCertifications: AWS Cloud Practitioner, AWS Solutions Architect Associate

Dr. Samuel Payne's lab member focused on proteomics analysis for survival risk in cancer patients.Created a standard procedure tutorial for survival analysis in our CPTAC package to teach researchers how to perform Cox's Proportional Hazard Test and create multivariate Kaplan Meier plots to track risk of negative outcomes (such as tumor recurrence or death) over time.Collaborated with several other research assistants in creating and improving our lab's CPTAC Python module (GitHub Repository: https://github.com/PayneLab/cptac).Focused on finding trends in protein enrichment for different groups of people, to eventually allow doctors and other researchers to query a cancer drug database to help doctors prescribe medicine that can manage abnormal protein levels.Skills developed: python programming, pandas, numpy, seaborn, survival analysis, Cox's Proportional Hazard test, proteomics analysis, gene-set enrichment analysis, REST APIs

Managed a team of 4 other student UX Designers (Technical Writers and a Graphic Designer) in creating a website for university cloud consultations. Check it out below!Researched, compiled, and created content for this website, ranging from explaining different cloud solutions (SaaS, PaaS, IaaS), to gathering and creating training resources for AWS and Azure, and creating pages for on-campus cloud user groups and trainings.Assisted in coordinating and carrying out user research, such as affinity diagrams, showcases, and Q&A sessions with our team of UX Designers.Skills developed: AWS fundamentals, project management, Agile methodologies, event planning and management

Researched and created documentation and charts on data security and analysis with PostgreSQL hosted in the cloud, and general cloud infrastructure. Gave recommendations for proper data security practices in the cloud, such as Identity Access Management (IAM), encryption, and general best practices for keeping data secure.Created documentation and instructions for other interns to access and query the secure database, and assisted in creating a data privacy agreement for other interns.Worked closely with the CEO and other interns to ensure data is stored, accessed, and analyzed securely.Skills developed: AWS troubleshooting (DNS, PostgreSQL), business strategy, cloud best practices

Assisted certified Physical Therapists by working with patients on prescribed exercises, applying ice and STEM therapy, and ice massages.Worked with a wide variety of people, from teenagers to the elderly, to assist them in recovering from surgeries and injuries.Skills developed: people skills, fundamentals of physical therapy, patient relations, clinic maintenance

House Manager and Stage Hand for various professional and student performances and events (conferences, summer camps, plays, concerts, musicals). Experience with Theater Management, maintenance and operations in order to have events run smoothly, even in the face of unexpected complications.Skills developed: house management, stage management, customer service, theatre setup/strike, event management, proper piano moving