We believe that success is derived from the combination of deep technical capabilities and strong industry domain knowledge. Whether you are a high-growth, agile startup or multinational public organization, Emergent Data can help drive scalable solutions in technical architecture, data strategy, governance, and machine learning infrastructure and development.

• Data Architecture Tech Lead, provided thought leadership and design for transforming data practices at Collective Health: data governance, data lake development, ingress/egress, schema evolution, and data/metadata catalogs.• Designed and implemented Data Warehouse models (conceptual, logical, and physical schemas), reducing the number of production pipelines by 50% and establishing a source of truth for analytical data. • Oversight of transactional data model design during migration from monolith to microservice architecture• Design and implementation of ETL/LT pipelines for Data Lake layers and Data Warehouse (Spark SQL, Pyspark, Databricks)

• Architecting Collective Health's Data Lake and establishing company wide data governance practices to improve efficacy of data-driven microservices, ML/analytic capabilities, and accuracy of internal and external reporting/metrics.• Built end-to-end data pipelines leveraging Airflow and Spark (Pyspark and SparkSQL), including schema design and modeling (logical and physical), ETL/LT mapping, and engineering production code. Fully implemented healthcare claims, subscription, CRM, platform analytics, and survey data pipelines.

• Updated ETL jobs to redesign underlying data models powering the company's BI tool (Looker), allowing for the creation of new metrics, increasing accuracy of existing metrics, and improving query efficiency by upwards of 400%.• Productionized gradient boost ML model for predicting high risk patient populations. Resultant risk scores integrated into the case management system to proactively identify and outreach high risk members and help drive the company's health outcome initiatives.

• People Manager for teams of up to eight associates performing data analysis and revenue cycle consulting for C-Suites and Senior Management of Fortune 500 Healthcare Systems.• Implemented ETL pipelines for new clients and improved existing ETL for internal claims grouping logic and transforms resulting in a 2x process efficiency increase.• Owned end-to-end analytics for large hospital networks and applied data mining and trending techniques in SQL, increasing teams’ YTD revenue risk identifications for hospitals by as much as 300%.• Built dashboards and improved reporting metrics using visualization tools (Power BI) to help streamline reporting processes and increase workflow efficiency.

• Engineered claims pricing algorithms to identify payment trends and recover revenue from governmental and commercial insurance carriers.• Utilized data visualization tools to consult hospital clients on systemic revenue cycle risk.

• Publication in Nature Genetics: Lis1 Regulates Asymmetric Division in Hematopoietic Stem Cells and in Leukemia. Feb 2, 2014.• Analyzed data sets and utilized data visualization techniques across multiple cell biology experiments to discover and articulate how upstream and downstream genetic markers affect the progression of mutations that cause Leukemia.• Leveraged experimental analysis to identify protein to protein interactions for a known genetic developmental inhibitor of blast crisis chronic myelogenous Leukemia.