The job, in the employer's words
Workana is the largest remote work platform for talent in Latin America. Our division focuses on matching exceptional professionals with leading and innovative companies around the globe.
About the Client
Our client is an innovative clinical development organization driving healthcare forward through advanced digital twins, AI/ML, and computational modeling. They partner with multidisciplinary teams across life sciences to translate complex biological and trial data into quantitative strategies that optimize clinical trial design, endpoint selection, and patient outcomes.
We are looking for an experienced Clinical Data Scientist specializing in Digital Twins, AI/ML, and Clinical Trial Simulation to join a multidisciplinary team of physicians, biostatisticians, pharmacometricians, and data engineers. This is a fully remote opportunity for professionals based in Latin America, working closely with an international team in an English-speaking environment.
Role Overview
As a Clinical Data Scientist, you will lead the development, evaluation, and application of digital twins to simulate virtual patients, disease trajectories, treatment responses, and clinical trials. You will work closely with cross-functional trial teams to translate clinical development questions into quantitative strategies, supporting key decisions across protocol design, patient selection, enrichment strategies, dosing, and operational planning.
In this role, you will combine mechanistic, statistical, causal, and machine learning models to build fit-for-purpose digital twins and reproducible analytical workflows. You will operate with high technical autonomy, bridging advanced AI/ML computational techniques with practical clinical trial design to inform decision-making under uncertainty.
Selection Process
The process usually consists of 4 stages and takes on average 4 weeks to be completed, depending on eventual additional technical rounds or take-home tests.
- Initial interview with Workana's recruiting team.
- Technical interview with Workana's technical team.
- Cultural fit interview with the client's manager
- Final interview with C-level
As Workana has multiple clients, if you pass the first round with Workana's recruiting team, you may also be considered for other relevant opportunities if the initial opportunity does not move forward.
Responsibilities
- 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
- 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.
Bonus Points
- 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
- 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.
Benefits mentioned
- 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.
Requirements mentioned
- 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.
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