NLP / LLM Data Scientist

Our Team

Dandelion Health https://dandelionhealth.ai/ was founded in 2020 by experts in health tech https://www.linkedin.com/in/elliott-green-98433b2/, hospital systems https://www.linkedin.com/in/niyum-gandhi/, academia https://sendhil.org/, and clinical AI http://ziadobermeyer.com/. 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 https://dandelionhealth.ai/team.

Our Data

We partner with health systems http://dandelionhealth.ai/team 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 https://dandelionhealth.ai/team – 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

You are a healthcare data scientist who knows your way around clinical and text-based data. Your primary responsibility will be to leverage and build upon large language models (LLM) and other ML-based approaches for meaningful data abstraction from both unstructured and structured healthcare data. You will join a team of data scientists who own the creation and maintenance of AI-ready datasets for clients in our environment. You will work across the organization to curate datasets by identifying patient subpopulations or disease cohorts, developing methodology to abstract information from multimodal healthcare data sources to support patient phenotyping, and pooling data to enable rapid exploratory AI/ML analyses, model experimentation and/or model validation. You will use your data expertise, programming abilities, and critical thinking skills to support our technical product team, and develop your own analyses to derive insights and enhance our datasets based on the use case. Your team’s ultimate goal is to deliver the highest-quality data possible to our clients, who are building products that improve patient health. You will report to the Data Science Manager, under the Head of Data.

Responsibilities

Your day-to-day responsibilities will include the following:

• Develop Natural Language Processing (NLP), Large Language Model (LLM) and other ML-based pipelines to abstract relevant labels from text-based healthcare data and store them in scalable data models;

• Query complex source systems in a range of health data sources (e.g., EMRs, semi-structured reports, free-text clinical provider notes) to identify key data elements and create and enrich high-quality datasets for real-world evidence analyses and training AI algorithms;

• Own data extraction, wrangling, labeling and QC tasks to create analytical datasets that include abstracted clinical concepts and provide a range of solutions to support customers’ AI activities;

• Stay current on the latest in applied NLP and generative AI methods and proactively leverage these technologies where applicable;

• Support the design, testing, validation, analysis, and merging of multimodal data structures from a wide variety of source systems;

• Develop code and documentation to deliver high-quality and HIPAA-compliant data products on time to customers;

• Identify and resolve problems using your knowledge, background,