Clinical Data Scientist - Digital Twins & AI/ML

Workana • Indianapolis, IN

9h • Remote

About The Position

Workana is recruiting for an innovative clinical development organization that uses digital twins, AI/ML, and computational modeling to advance healthcare. The organization works with multidisciplinary life-sciences teams to translate biological and clinical-trial data into quantitative strategies for clinical-trial design, endpoint selection, and patient outcomes.

The Clinical Data Scientist will lead the development, evaluation, and application of digital twins to simulate virtual patients, disease trajectories, treatment responses, and clinical trials. The role works with cross-functional trial teams to turn clinical-development questions into quantitative strategies that inform protocol design, patient selection, enrichment, dosing, and operational planning.

The scientist will combine mechanistic, statistical, causal, and machine-learning models to build fit-for-purpose digital twins and reproducible analytical workflows. The role requires substantial technical autonomy and collaboration with physicians, biostatisticians, pharmacometricians, data engineers, and other international team members in an English-speaking environment. The posting describes the role as fully remote for professionals based in Latin America, while its benefits section also mentions hybrid work in Indianapolis or fully remote work within the U.S. East Coast, with occasional travel.

The selection process usually has four stages and takes an average of four weeks, potentially including additional technical rounds or take-home tests: an initial Workana recruiting interview, a technical interview with Workana, a cultural-fit interview with the client's manager, and a final interview with a C-level executive. Candidates who pass the initial Workana recruiting round may also be considered for other relevant opportunities.

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.

Nice To Haves

• 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 such as AWS, GCP, or Azure.
• Experience working with clinical-data standards and multimodal biomedical-data integration.

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 multimodal 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 with biostatisticians and pharmacometricians to ensure digital-twin outputs complement established trial-design methods.
• Ensure model quality, interpretability, auditability, and responsible use by defining decision contexts, success criteria, and limitations.
• Communicate model assumptions, uncertainty, and decision-relevant insights to technical and non-technical stakeholders.

Benefits

• Competitive salary.
• Travel expenses covered when travel is required.
• Flexible work arrangements, described as hybrid in Indianapolis, Indiana, 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree