Translational AI Engineer - Clinical Informatics

BioSpace; Boston (MA); On-site; USD 167,000 - 266,000; Full time

Benefits offered by this job

Company bonus

401(k)

Pension

Vacation benefits

Medical, dental, vision

Job summary

Lilly is seeking a highly specialized Applied AI Engineer Clinical Informatician to lead research at the intersection of completed clinical trial datasets and biobank-linked population data. This hands-on role focuses on building systems to extract and contextualize patient phenotypes for translational insights.

The candidate will work with locked trial databases, real-world data, and biobank cohorts, developing AI/ML solutions to enable analysis and discovery while adhering to data governance

Qualifications

• MS in Biomedical Informatics or equivalent with 6+ years of research experience with clinical trial data, biobank data, or large-scale population health data
• PhD in Biomedical Informatics or equivalent with 3+ years of research experience in similar datasets

Responsibilities

• Develop AI/ML applications enabling NLP interactions with clinical data
• Ground AI outputs in validated biological knowledge using ontologies and registries
• Deploy unsupervised/self-supervised learning to identify patient archetypes and subtypes
• Build AI/ML systems to harmonize trial/biobank data into common representations
• Monitor model performance, safety, and reliability in production environments

Skills

Python

R

SQL

Biobank data

NLP

Survival analysis

Education

MS in Biomedical Informatics

MD/PhD with translational data science

PhD in Biomedical Informatics

MD/PhD

MS in Computational Biology

Tools

DNAnexus

AWS

GCP

Azure

HPC clusters

CDISC SDTM/ADaM

Job description

Lilly is seeking a highly specialized Applied AI Engineer Clinical Informatician to lead research at the intersection of completed clinical trial datasets and biobank-linked population data. This hands-on role focuses on building systems to extract and contextualize patient phenotypes for translational insights.

The candidate will work with locked trial databases, real-world data, and biobank cohorts, developing AI/ML solutions to enable analysis and discovery while adhering to data governance