Member of Technical Staff, Principal Biostatistician

About the role

Join a clinical AI research lab focused on precision medicine and multi-modal AI. This role involves developing new AI methods to predict patient outcomes and treatment responses. You will contribute to building clinical tools that help physicians select optimal treatments. The position sits at the intersection of advanced computational modeling and real-world clinical evidence, driving innovation in oncology and related therapeutic areas. You will be responsible for ensuring the statistical rigor and reproducibility of high-impact AI projects from conception to deployment. Collaboration with world-class engineers and clinical scientists will be central to your day-to-day responsibilities. This role demands intellectual curiosity and the ability to translate complex analytical findings into actionable medical insights. Ultimately, your work will directly influence how precision medicine tools are designed and validated for clinical use.

Key facts

What you'll do

• Design and implement statistical evaluation frameworks to rigorously assess the performance and safety of Ataraxis AI models in simulated clinical environments.
• Draft and submit applications to obtain access to sensitive data from completed clinical trials, ensuring all regulatory and ethical standards are met.
• Conduct in-depth audits of AI models by analyzing outputs against historical data from finished clinical trials, focusing on accuracy and generalizability.
• Orchestrate cross-functional workflows with a diverse team of engineers, clinicians, and scientists to align project goals and timelines.
• Lead participation in multi-site research projects with academic and industry collaborators, contributing to study design and analysis interpretation.
• Translate complex model outputs into regulatory-ready documentation to support submissions to oversight bodies and institutional review boards.
• Distill sophisticated analytical results into clear narratives for both technical and non-technical audiences, contributing to peer-reviewed scientific papers and high-stakes presentations.
• Mentor junior biostatisticians and data scientists, providing expert guidance on study design, coding standards, and validation methodologies.
• Champion reproducible research practices by developing and maintaining robust code libraries, version control systems, and detailed analytical documentation.
• Identify gaps in existing clinical data structures and collaborate with data engineering teams to optimize datasets for advanced modeling techniques.
• Explore the integration of emerging machine learning evaluation metrics to enhance the interpretability and trustworthiness of AI-driven clinical predictions.
• Establish quality assurance protocols to detect and mitigate biases in AI models trained on heterogeneous biomedical data sources.
• Synthesize findings from diverse analytical streams to support strategic decisions regarding product development and clinical validation pathways.
• Act as a statistical domain expert in leadership discussions, prioritizing analytical roadmaps based on scientific merit and operational feasibility.

Requirements

• Hold a PhD in statistics or biostatistics, or demonstrate equivalent practical experience through a robust portfolio of applied research.
• Maintain a strong history of published work in biostatistics in peer-reviewed journals, with a record of contributions to the methodological community.
• Bring substantial experience creating statistical analysis plans for clinical study data, with a proven track record in oncology clinical trial settings.
• Exhibit strong problem-solving skills, adept at navigating ambiguous scientific questions and developing innovative analytical approaches.
• Demonstrate excellence in data visualization, using graphical methods to reveal insights and communicate uncertainty effectively to diverse stakeholders.
• Adhere strictly to reproducible research methods, ensuring that all analyses are transparent, scalable, and independently verifiable.
• Show expert-level command of Python and R, with a portfolio of projects showcasing efficient, well-documented code.
• Display proficiency in managing large, intricate biomedical datasets, including genomic, imaging, and longitudinal clinical information.
• Cultivate deep knowledge of survival analysis, Bayesian statistical methods, and causal inference frameworks to address complex clinical questions.
• Possess the ability to work independently with minimal supervision while maintaining rigorous attention to detail and data integrity.
• Secure the ability to obtain necessary security clearances and comply with institutional policies governing protected health information.
• Commit to ongoing professional development to keep pace with rapid advancements in AI, biostatistics, and regulatory science.
• Thrive in a dynamic startup environment where roles evolve quickly and adaptability is a core requirement for success.
• Demonstrate strong written and verbal communication skills essential for collaborating with interdisciplinary teams.

Nice to have

• Familiarity with contemporary machine learning techniques and their application in clinical validation workflows.

Practical notes

Ataraxis has secured over $24 million in funding, including a $20 million Series A. The company operates with a flat organizational structure, encouraging active contributions from all team members. Leadership opportunities are based on initiative and consistent, exceptional performance. A strong work ethic and the ability to prioritize effectively are essential.