Software Developer - Python

About The CompanyMcKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care.We foster a culture where growth, innovation, and impact are at the forefront. Our commitment to improving healthcare outcomes drives us to develop advanced solutions and collaborate with industry leaders. At McKesson, you will find a dynamic environment that encourages continuous learning and professional development, empowering you to make meaningful contributions to the future of health.Our global presence and diverse workforce enable us to address complex healthcare challenges and deliver value across the healthcare spectrum. Join us in shaping the future of healthcare and making a difference in people's lives worldwide.About The RoleThe Senior Associate Software Developer at McKesson plays a crucial role in advancing our retinal health initiatives through sophisticated data management and analysis. This position involves working with clinical and administrative ophthalmology data to build and refine data sets and models that support research and real-world evidence studies. The successful candidate will be responsible for extracting, integrating, and analyzing complex medical images and datasets from various sources, including proprietary imaging formats and APIs.This role requires a deep understanding of ophthalmology-specific data, including retinal imaging modalities such as OCT, fluorescein angiography, and wide-field imaging. The developer will collaborate with cross-functional teams to ensure system improvements are effectively implemented, monitored, and optimized for efficiency. The position offers the flexibility of 100% telecommuting from any location within the United States, with occasional travel (approximately 15%) domestically or internationally for meetings, conferences, or project-related activities.The ideal candidate will leverage their expertise in clinical research methods, data science, and software development to prepare datasets that support innovative research, clinical trials, and product development within the RetinaOS platform. This role is integral to enhancing ophthalmic data analysis, image processing, and model development, ultimately contributing to improved patient outcomes and advancing ophthalmology research.QualificationsThe successful candidate must possess a Master’s degree or foreign equivalent in Computer Vision, Computer Science, or a related field, along with at least three years of relevant experience in a research or healthcare setting. Demonstrated expertise in preparing data for research studies, real-world evidence projects, and clinical applications is essential.Additionally, the candidate must have at least one year of proven experience in the following areas:Retinal and ophthalmology-specific electronic medical records, database integration, coding, and clinical data management, including ophthalmology imaging, data modeling, and statistical and computer vision models for retinal images.Proficiency in Python programming, cloud computing, and working with medical images, especially in anterior and posterior ophthalmology.Linking electronic medical records with practice management and imaging data to create comprehensive, longitudinal patient records.Expertise in computer vision techniques related to ophthalmology, such as image segmentation, object detection, and lesion analysis.Experience in retinal image processing, volumetric rendering, and measurement techniques.Programmatic extraction of data from proprietary ophthalmic imaging formats from vendors like Carl Zeiss, Heidelberg Engineering, Topcon, Nikon/Optos, among others.SQL query development, troubleshooting, and visualization, with a focus on optimizing queries for clinical and administrative datasets containing PHI.Building data science pipelines in AWS cloud environments, including data parsing, linking records, processing PHI, and modeling.Development of Robotic Process Automation (RPA) applications within cloud settings.Proficiency with development tools such as VS Code IDE, Jupyter Lab, and security tools like Veracode.Advanced statistical analysis and data modeling, including descriptive and inferential statistics specific to ophthalmology datasets.Experience in building drug-switch matrices, patient care analyses, and other clinical data analyses related to retinal health.Furthermore, the candidate should have demonstrated experience with various ophthalmic imaging modalities, including OCT, wide-field imaging, and fluorescein angiography, as well as proficiency in Postgres SQL (version 16+ with extensions).ResponsibilitiesDevelop and maintain data sets and models for retinal clinical and administrative data, ensuring accuracy and reliability for research and clinical applications.Extract, process, and integrate ophthalmology imaging data from diverse proprietary formats and sources, ensuring data integrity and compatibility.Apply computer vision techniques to analyze retinal images, including segmentation, lesion detection, and volumetric measurements.Collaborate with clinical researchers, data scientists, and software engineers to prepare datasets for research studies, clinical trials, and real-world evidence projects.Design and implement data pipelines in AWS cloud environments for parsing, linking, and modeling ophthalmology data, ensuring compliance with privacy and security standards.Develop RPA solutions to automate data processing tasks, improving efficiency and reducing manual effort.Optimize SQL queries for clinical and administrative datasets, troubleshoot issues, and create visualizations for data insights.Ensure system improvements are effectively deployed, monitored, and refined to enhance performance and user experience.Support the integration of clinical data with imaging data, creating comprehensive patient records that facilitate longitudinal studies and analytics.Participate in cross-functional meetings to align data strategies with project goals and