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Zus Health
2021–2023
Principle Software EngineerI led core strategic data management products and the use of safe & innovative Artificial Intelligence applications in healthcare for Zus Health.
I have previously led to GA our data usability strategy products running teams ranging from 1 - 12 contributors. I have built
Our AI enabled Hybrid Search pipeline with Retrieval Augmented Generation for query answering and patient data summarization to unlock previously inaccessible workflows in patient care, and build clinical decision support tools to empower clinicians.
Our foundational real-time Master Patient Index with a sub-500 ms 99th percentile SLA. All other Zus products depend on this.
Our streaming medical record data reconciliation and summarization layer. This enables Zus’ collaborative patient longitudinal record.
Our serverless data normalization preprocessor which standardizes data formatting and terminology values across ICD-10, SNOMED, RxNorm, and LOINC.
In addition to my technical responsibilities
Routinely work with CTO & CPO, and share out weekly company wide updates and demos
Manage cross-functional efforts including legal, commercial, and infra coordination for BAA’s, and customer interviews
Mentored junior engineers with paired programming, lunch talks, and weekly check-ins
Omada Health
2019–2021
Data Scientist & Machine Learning EngineerI led development of all data science products for coaching insights and quantification of behavior change towards company’s KPI of participant weight loss across a team of 8 data scientists at Omada Health
Built the ML model development and deployment pipeline that enabled our team which had not launched a product in years to immediately ship 4 new projects, with a reusable pattern the entire team adopted.
Led cross functional partnerships with clinical research and finance increasing data literacy and trust across the organization.
Launched the revenue forecasting, churn emailing, weight-logging filtering, and participant message emotion classification models, and content personalization.
Created intent and emotion classification on participant messaging for mental state correlations to OKRs and coaching intervention design.
Built and ran a highly engaged, voluntary data labeling competition resulting in a ground-truth dataset of millions of examples, enabling problem-sizing the error rates affecting our chief revenue source. Presented the findings company-wide
Trained an explainable logistic regressor on my acquired dataset reducing the error rates from 3% to 0.3%, directly improving revenue, participant experience, support staff efficiency, and audit risk.
UMass Amherst
2018–2020
Master's Degree in Data ScienceI completed my Master’s degree in Computer Science with a concentration in Data Science at UMass Amherst, while working at Omada. My coursework included Neural Networks, Data Visualization, Business Management, and Applied Behavioral Interventions.
Einstein AI, Salesforce
2016–2018
Member of Technical Staff I worked with the Einstein.ai Salesforce team out of Palo Alto, CA as a back-end engineer on deep-learning products.
Developed restful API microservices
Replaced legacy deep learning framework with a Tensorflow implementation
Created patented deep learning image data augmentation utility
Terrapower
2014–2016
Nuclear Science & Engineering: Computer Scientist L2 I worked on a proprietary nuclear reactor design and analysis software at Terrapower in Seattle, WA.
Co-wrote patented nuclear reactor life cycle simulation software including graphical interface
Established CICD, coding best-practices, tests, input validations, and project dashboard with reactor simulation analysis reporting
I am interested in continuing my work in either cutting edge artificial intelligence development companies or innovative healthcare companies.
I have primarily coded with Python and Golang.
