Remote Data Architect
WRS Health
πRemote - Worldwide
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Job highlights
Summary
Join our team and play a pivotal role in building robust data infrastructure to support reporting across multiple departments.
Requirements
- Master's degree in Computer Science, Statistics, Mathematics, or a related field
- Proven experience as a Data Scientist with a strong focus on data architecture and engineering
- Strong expertise in data storage, containers, and structures, with experience in FHIR, JSON, XML, HL7, and x12 metadata standards
- Solid understanding of data exchange protocols and standards in healthcare, including FHIR APIs, Surescripts, and X12 messages
- Proficiency in data visualization tools (e.g., AWS Quicksight), machine learning (SageMaker), and AI platforms (Bedrock, Amazon Q)
- Expert-level proficiency in data structures, algorithms, and database design
- Strong proficiency in Python or similar programming languages
- Experience with data visualization tools (e.g., Tableau, Power BI)
- Excellent analytical and problem-solving skills
- Strong communication and interpersonal skills to effectively collaborate with stakeholders
- Experience in the Healthcare industry and Hubspot is a plus
Responsibilities
- Design, develop, and implement data architectures and pipelines to efficiently collect and process data
- Create complex data models and structures to accommodate diverse data sources and support advanced analytics
- Develop and maintain comprehensive reports, analysis and dashboards to provide actionable insights for various departments, including but not limited to finance, operations, clinical, and marketing
- Design and manage data containers, storage, and retrieval systems for WRS Health's data assets, including patient data, IoT, genome, microbiome, and government datasets
- Develop and maintain data structures using FHIR, JSON objects, XML, and HL7/x12 metadata standards to facilitate data exchange and interoperability
- Manage the use of data tools and AWS technologies, including AWS Quicksight, SageMaker, Bedrock, and Amazon Q, to enhance data mining, visualization, and AI-driven solutions
- Ensure the secure and efficient exchange of data, including FHIR resources, Surescripts record locators, and various healthcare data standards (e.g., CCDA, NCPDP, X12 messages)
- Implement machine learning models using SageMaker and AI large language models through Bedrock
- Configure AI solutions to enhance business and clinical operations with Amazon Q
- Work closely with stakeholders to understand their reporting requirements, translate them into technical specifications, and deliver solutions that meet their needs
- Ensure data integrity, accuracy, and consistency through rigorous quality control measures
- Continuously explore new data technologies and methodologies to enhance reporting capabilities and drive business value
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