US-Based Healthcare Data Scientist

TL;DR

US-Based Healthcare Data Scientist (NLP/LLM): Train, fine-tune, and enhance LLM & NLP models for clinical data analysis using Python libraries and Spark NLP, building production-ready inference pipelines. Focus on extracting insights from medical text/images, integrating multi-source data, validating for bias/overfitting/drift, and collaborating on customer projects in healthcare.

Location: US-Based. Fully virtual company collaborating across 28 countries, but this role is US-Based. Contract requires 30-40 hours per week availability.

Company

Award-winning AI and NLP company providing software, data, and models for healthcare and life sciences, developers of Spark NLP, with a global team of PhD/MD specialists.

What you will do

• Train, fine-tune, and enhance LLM & NLP models using open-source Python libraries.
• Build data science and engineering pipelines for clinical data analysis, including medical text/images and multi-source integration.
• Collaborate on customer-facing projects creating ML, deep learning, LLM, and time series forecasting pipelines.
• Validate models for bias, overfitting, and concept drift.
• Engage directly with customers, communicating complex technical concepts.

Requirements

• Proven real-world project delivery experience covering key responsibilities (not just academic or API usage).
• Hands-on with OMOP, FHIR, clinical terminologies, and patient journey understanding.
• Strong healthcare background (medicine, pharma, bioinformatics, biostatistics).
• PhD preferred, or exceptional relevant experience.
• Strong oral/written communication for customer interaction.

Nice to have

• Experience with Spark NLP or hirify.global’ medical models.
• Experience with LLMs, Generative AI, deep learning.

Culture & Benefits

• Fully virtual collaborative environment across 28 countries.
• Work on cutting-edge healthcare projects impacting patient outcomes.
• Long-term freelancing contracts (30+ hours/week), skill growth with data science experts.
• Commitment to diversity and innovation.