About The Role

Join Horizon Surgical Systems as a DataOps Analyst, where you'll work closely with our principal DataOps engineer and play a crucial role in managing surgical data and supporting our AI model training. This hands-on position is perfect for early-career professionals looking to make a meaningful impact in medical AI.

Move and manage surgical data between Polaris and the AWS cloud training environment, ensuring pipelines are healthy and well-documented.
Build and maintain ETL/ELT workflows using Python and Bash, and help improve their reliability over time.
Collaborate with AI/ML engineers to curate, version, and validate training and test datasets, and support data requests from cross-functional teams.
Git-fluent: version control is part of your daily workflow, not an afterthought
Solid understanding of the AWS ecosystem (S3, Lambda, Glue, or similar services)
Bachelor's degree in Computer Science, Data Science, or a related field — or equivalent hands-on experience
2+ years of experience in a data operations, data engineering, or data analysis role
Good communicator — you can work with technical and non-technical stakeholders without losing them
You take data quality seriously and document your work clearly
Comfortable working in Linux environments and writing Bash scripts
Proficiency in Python for data manipulation, scripting, and automation
Experience in a medical, clinical, or regulated environment (FDA, ISO 13485, or similar)
Background in image processing or computer vision workflows
Knowledge of statistics — data distributions, sampling methods, quality metrics
Familiarity with DICOM or ophthalmic imaging data (OCT, surgical microscopy)
Exposure to ML data lifecycle concepts: dataset versioning, data drift, model validation sets

This is an external listing. JobSpring does not represent or verify the employer. Report this listing