All Of Our Groups
healthcare
AppliedAIEngineer,ClinicalInformatics
“Applied AI Engineer, Clinical Informatics at All Of Our Groups. Skills: AI, Machine Learning, Clinical Data, Bioinformatics. Develop and deploy agentic AI applications. Ground AI outputs in validated biological knowledge”
What You'll Achieve.
Generate translational insight; Shape the next generation of clinical research
Industry & Context.
Thinks like a scientist
What They're Looking For.
Must Have
M.S. in Biomedical Informatics, Computational Biology, Bioinformatics, Statistical Genetics, Epidemiology, or a closely related quantitative field or an MD/PhD with equivalent depth in translational data science with 6+ years of research experience working with clinical trial datasets (SDTM/ADaM), biobank data, or large-scale population health data in an academic, pharmaceutical, or research institute setting, Ph.D. in Biomedical Informatics, Computational Biology, Bioinformatics, Statistical Genetics, Epidemiology, or a closely related quantitative field or an MD/PhD with equivalent depth in translational data science with 3+ years of research experience working with clinical trial datasets (SDTM/ADaM), biobank data, or large-scale population health data in an academic, pharmaceutical, or research institute setting
Nice to Have
Demonstrated use of AI tools in production environments for clinical data analysis, Expert proficiency in Python and/or R for statistical modelling and command of SQL and experience with cloud-based research computing environments (ideally DNAnexus, AWS, GCP, Azure, or HPC clusters), Familiar with advanced generative AI methods like finetuning of LLMs. Building and training foundation models from scratch. High performance computing environments, Deep knowledge of CDISC standards (SDTM, ADaM) and experience analyzing clinical trial databases for secondary research purposes, Demonstrated experience applying ML methods including survival analysis, causal inference, NLP, and deep learning to clinical or genomic research questions, Thorough understanding of OMOP CDM, HL7 FHIR Genomics, and major biomedical ontologies, Direct research experience with major public and restricted-access biobank resources (UK Biobank, All of Us, etc.), Experience with federated learning, differential privacy, or secure computation frameworks applied to multi-site biomedical research, Track record of peer-reviewed publications in clinical AI, translational informatics, genomics, or a related field, Familiarity with the target trial framework and its application in biobanks, Knowledge of pharmacogenomics, drug response modeling, or PK/PD data analysis from clinical trials, Experience with knowledge graph construction, graph ML, or ontology-driven reasoning for biomedical discovery, Hands-on experience with multi-omic data analysis
What You'll Do.
Develop and deploy agentic AI applications
Ground AI outputs in validated biological knowledge
Implement RAG pipelines
Deploy unsupervised and self-supervised learning approaches
Discover latent patient archetypes
Discover molecular disease subtypes
Deploy survival models
Deploy dynamic treatment regime estimators
Harmonize heterogeneous datasets
Evaluate and monitor model performance
Manage vendors and contractors
Partner with relevant teams
Build pipelines for clinical trial databases
Conduct secondary research
Conduct exploratory research
Identify trial subgroup effects
Identify treatment heterogeneity
Identify responder/non-responder signatures
Mine adverse event narratives
Mine investigator comments
Surface latent safety signals
Reconstruct patient-level trajectories
Model disease progression
Model drug response kinetics
Model time-to-event outcomes
Architect workflows for meta-analytic analyses
Architect workflows for cross-trial analyses
Identify generalizable patterns
Build connections to biobank cohorts
Establish research data management practices
Ensure reproducibility of analyses
Ensure compliance with HIPAA
Ensure compliance with GDPR
Ensure compliance with IRB
Ensure compliance with ethics committees
How You'll Work.
Team & Collaboration
Work with partners across Lilly; Partner relationships with relevant teams
Communication Scope
Communicates like a clinician
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