Job Description

The Center for Data Science in Emergency Medicine (CDEM) at the Johns Hopkins School of Medicine is seeking a passionate Software Engineer to join our dynamic research team. In this role, you won't just be writing code – you'll be improving healthcare delivery and patient outcomes through your contributions to the development of artificial intelligence-enabled clinical decision support. Do you thrive where technology meets medicine? At CDEM, we believe the future of healthcare hinges on collaboration between brilliant minds in medicine and engineering. Here, you won't just be a software engineer; you'll be an innovator directly impacting patient lives. Your code will have a real-world consequence, improving the well-being of thousands. This is your chance to embrace a challenging and rewarding role at the forefront of healthcare technology.



Specific Duties & Responsibilities
Troubleshoot and optimize performance of large-scale SQL databases within Azure using advanced query tuning techniques. Ensure high availability and scalability for healthcare data pipelines.
Develop and maintain data dictionaries to standardize data definitions across the team. Lead weekly code reviews to ensure adherence to best practices for data cleaning, transformation, and analysis.
Document code using industry-standard tools (e.g., Sphinx) and maintain a version control system (e.g., Git) to facilitate collaboration and code rollback if necessary.
Develop clear and concise user stories and technical documentation for complex data science projects. Utilize data visualization tools (e.g., Tableau, PowerBI) to effectively communicate workflows to non-technical stakeholders.
Develop and implement machine learning models (e.g., Random Forests) to predict patient readmission risks or identify potential fraud cases within healthcare claims data.
Develop and maintain secure and scalable healthcare applications using frameworks like USCDI that seamlessly integrate with Epic EHR for improved clinical decision support.
Develop expertise in the medical domain by actively acquiring a strong understanding of medical terminology, disease processes, and relevant clinical data. This knowledge will be used to effectively analyze and interpret healthcare datasets for AI model development.
Translate medical knowledge into actionable insights: You will act as a bridge between the medical and data science worlds. By understanding the medical context and implications, you'll translate complex medical information into a format suitable for machine learning algorithms.
Stay abreast of cutting-edge advancements in AI (e.g., Generative AI for synthetic data generation) and healthcare technology (e.g., wearable biosensors) by attending industry conferences and workshops. Proactively research and integrate these advancements into ongoing projects to improve efficiency and accuracy.
Mentor junior developers by conducting code reviews, providing constructive feedback, and offering guidance on best practices for designing, developing, and testing healthcare applications. Develop and deliver training sessions on new technologies and healthcare data management tools.
Champion innovative approaches to healthcare software development. Conduct research to identify emerging technologies and propose novel solutions that integrate seamlessly with existing healthcare infrastructure. Present findings and recommendations to leadership to influence the future direction of healthcare software development within the team.


Special Knowledge, Skills & Abilities

Experience with accessing and retrieving data in common database platforms using Microsoft SQL Server, including developing and maintain stored procedures and functions.
Thorough knowledge of, and demonstrable experience, with multiple programming languages including Python and SQL.
Experience interpreting and analyzing healthcare data (e.g., Epic, Cerner).
Ability to work within multiple operating systems including Windows, Unix and Docker.


Minimum Qualifications
Bachelor's Degree.
Five years related experience.
Additional education may substitute for required experience and additional related experience may substitute for required education, to the extent permitted by the JHU equivalency formula.


Preferred Qualifications
Experience with cloud integration (Azure preferred)
Prior experience with healthcare data and, in particular, EPIC clarity/caboodle databases.
Prior experience with common healthcare APIs and interoperability standards including HL7 version 2 and FHIR/SMART on FHIR.
Advanced capabilities in SQL-MS SQL (including T-SQL, ability to create views, stored procedures, SSIS packages, user defined functions, etc.)
Web app platforms: Vue.JS or similar JavaScript framework.
Experience with source control: SVN, Git and Gitlow.