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Software Engineer

Remote role Full-time Open position

Our Team

Dandelion Health was founded in 2020 by experts in health tech, hospital systems, academia, and clinical AI. We are building the world’s largest AI training and clinical development platform. Today, we pride ourselves on our ability to make data access as easy as possible for AI developers, pharma, and medical devices, while raising the bar for patient safety and data quality. Tomorrow, we will be the place where any healthcare organization can go to build a responsible clinical AI product. Our culture is all about learning from data and improving, so we can help our clients improve health through AI. Meet the rest of our team here.

Our Data

We partner with health systems to safely and ethically make their de-identified patient data available to AI developers. Currently, the data is acquired from Sharp HealthCare, Sanford Health, and Texas Health Resources – with two additional U.S. health systems joining soon.

We have clinical data dating back to July 1, 2016. This data represents over 10 million patients and includes but is not limited to:

  • Structured data (e.g., 100% of the EMR, including some claims)

  • Unstructured text (e.g., clinical notes, radiology reports)

  • Images (e.g., DICOM, pathology)

  • Video

  • Waveforms

  • Continuous streaming monitoring data

Your Role

Dandelion is constantly expanding the breadth, depth, and completeness of health system datasets while improving the speed and quality of our de-identification pipeline. As an engineer working on our de-identification pipelines, you will:

  • Design and implement software systems that perform these de-identification rules at high scale and throughput (we de-identify billions of rows of data and millions of images each month) while constraining costs.

  • Generate and execute quality assurance plans to validate our de-identification processes.

  • Run de-identification pipelines in health system cloud environments, and optimize these pipelines to minimize error rates, improve processing efficiency, and reduce manual effort and cost.

  • Partner with our Director of Privacy and Clinical Informaticists to define de-identification rules.

Required technical skills

  • 3+ years of development experience in Python or an equivalent language in a professional setting, across the full software development lifecycle (design, implementation, testing, deployment, maintenance);

  • Familiarity with one or more command languages (e.g. Bash) and SQL.

Required Non-technical skills

  • Demonstrated ability to design and improve workflows, including associated operating procedures, cost management, and quality assurance;

  • Strong analytical decision-making and organizational skills;

  • Perseverance and practical problem solving;

  • Humility and strong team collaboration;

  • Enthusiasm about protecting patients’ personal data.

We are an AWS and Python shop, and our datasets are stored in AWS Redshift, Snowflake, or Parquet files which are processed in Pandas DataFrames.

Preferred skills

  • Proficiency with data structures such as Pandas DataFrames;

  • Previous software deployment in a cloud computing environment (e.g., AWS, Azure);

  • Familiarity with virtualization and containerization (e.g., Docker, VMware);

  • Prior experience working with healthcare data;

  • Experience interacting with non-technical stakeholders to deploy software solutions.

Team Benefits

  • Remote work and flexible hours. Availability needed for meetings, which we try to keep to a healthy minimum

  • Complete wellness benefits including healthcare, dental, vision, PTO, sick days and more. Ask for details

  • Professional development days to build your skills

  • Collegial work environment

  • Academic bent towards inquiry and problem solving but start-up speed and flexibility

  • Great balance of focus time to work on projects but easy to access team members to discuss issues and work collaboratively

  • Dandelion is a mission-driven company that is focused on improving patient care

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