Principal Biostatistician, AI Oncology & Survival Analytics

Ataraxis AI; New York (NY); On-site; USD 120,000 - 170,000; Full time

Job summary

Ataraxis AI is a clinical AI research lab focused on predicting patient outcomes and treatment responses through multi-modal data. The role involves designing evaluation plans, accessing trial data, and collaborating across engineers, scientists, and external partners to advance regulatory submissions and publications.

The ideal candidate holds a PhD in statistics/biostatistics with a track record in oncology data, survival analysis, Bayesian methods, and causal inference, plus strong Python/R

Qualifications

• PhD in statistics/biostatistics with strong publications in biostatistics.
• Experience developing statistical plans for analysis of clinical studies, especially oncology.
• Strong problem-solving, data visualization, and reproducible research practices.
• Excellent Python and R skills; comfortable with large biomedical datasets.
• Expertise in survival analysis, Bayesian methods and causality.
• Familiarity with modern machine learning methods.

Responsibilities

• Design and implement statistical evaluation plans for Ataraxis AI models.
• Write applications to access data from completed clinical trials.
• Evaluate AI models on data from completed clinical trials.
• Collaborate with a multidisciplinary team of engineers and scientists.
• Collaborate on research projects with academic and industrial partners.
• Contribute to regulatory submissions.
• Present findings to stakeholders and contribute to publications.
• Mentor junior biostatisticians and data scientists.

Skills

Python

R

Survival analysis

Bayesian methods

Causality

Data visualization

Education

PhD in statistics/biostatistics

Job description

Ataraxis AI is a clinical AI research lab focused on predicting patient outcomes and treatment responses through multi-modal data. The role involves designing evaluation plans, accessing trial data, and collaborating across engineers, scientists, and external partners to advance regulatory submissions and publications.

The ideal candidate holds a PhD in statistics/biostatistics with a track record in oncology data, survival analysis, Bayesian methods, and causal inference, plus strong Python/R