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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing digital twins and computational models for healthcare applications, utilizing advanced machine learning and statistical techniques. Proficient in collaborating with clinical trial teams and integrating multi-modal datasets to inform drug development decisions.
Highest-signal resume keywords
PhD In Data ScienceDigital Twin DevelopmentMachine Learning ApplicationAdvanced Programming In PythonClinical Trial Design Support
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Statistical ModelingCausal InferenceBayesian ModelingSurvival AnalysisLongitudinal ModelingAdaptive Trial DesignSimulationModel-Informed Drug DevelopmentData IntegrationQuantitative Research
Soft Skills
Problem-SolvingCommunication
Tools & Technologies
AWSGCPAzureVersion-Controlled WorkflowsReproducible Workflows
Industry Keywords
Clinical TrialsBiomedical DataPharmaceuticalsDigital HealthReal-World Data
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformPython
About the role
Key responsibilities & impact- Lead the design, development, calibration, and validation of digital twins for patients, disease progression, and trial outcomes using clinical trial and external data.
- Combine machine learning, statistical modeling, causal inference, and mechanistic approaches to build fit-for-purpose computational models.
- Partner with trial teams to evaluate protocol design options, including target populations, eligibility, enrichment strategies, endpoints, and dosing.
- Analyze and integrate multi-modal datasets, including clinical trials, biomarkers, real-world data, digital health, imaging, and omics.
- Collaborate with data engineering and platform teams to build reproducible pipelines, reusable digital-twin components, and analysis-ready datasets.
- Work alongside biostatisticians and pharmacometricians to ensure digital-twin outputs complement established trial-design methods.
- Ensure model quality, interpretability, auditability, and responsible use by defining clear decision contexts, success criteria, and limitations.
- Communicate model assumptions, uncertainty, and decision-relevant insights clearly to technical and non-technical stakeholders.
Requirements
What you’ll need- PhD in Data Science, Statistics, Biostatistics, Pharmacometrics, Computer Science, Biomedical Informatics, or a related quantitative field.
- Demonstrated experience developing digital twins, virtual patients, disease-progression models, or clinical trial simulations.
- Strong experience applying machine learning, statistical modeling, causal inference, or simulation to healthcare, pharmaceutical, or complex biomedical data.
- Advanced programming skills in Python or R, with experience using version-controlled and reproducible workflows.
- Sufficient clinical-development knowledge to frame quantitative research questions and collaborate effectively with trial experts.
- Strong problem-solving skills and ability to translate complex analytical results into actionable clinical development decisions.
- Direct experience supporting clinical trial design, protocol development, model-informed drug development (MIDD), or regulatory-facing quantitative evidence.
- Expertise in Bayesian modeling, survival analysis, longitudinal modeling, adaptive trial design, or synthetic control arms.
- Experience working with scalable cloud-based analytical environments (AWS, GCP, or Azure).
- Experience working with clinical data standards and multi-modal biomedical data integration.
Benefits
Comp & perks- Competitive salary with travel expenses covered when travel is required
- Flexible work arrangements (Hybrid in Indianapolis, IN, or Fully Remote within the U.S. East Coast with occasional travel)
- Dynamic career growth with innovative, high-impact enterprise projects
- Long-term independent contractor agreement