Principal, Biostatistician, Roivant Health

Roivant Sciences, Inc., 1 Pennsylvania Plaza, 54th floor, New York, NY 10119, United States

Since its inception in 2014, Roivant Sciences has sought to improve health by rapidly delivering innovative medicines and technologies to patients. We've employed a unique, decentralized model of nimble, focused companies ("Vants") centered on innovation in drug development and technology. Five new medicines have been approved off the Roivant platform, we've built multiple biotechs that have become public companies, and we've created substantial value across the platform spanning computational drug discovery, healthcare data exchange, and novel therapeutic platforms.

Roivant Health is Roivant’s platform for the creation of new technology Vants, focused on delivering improvements to human health outside of our traditional biotech platform. In six years since inception, we’ve created eight enduring companies and over $1B in enterprise value, including the leading deidentified healthcare data exchange platform (Datavant) and a top-tier computational drug discovery company (VantAI) which has partnered with Johnson & Johnson, Bristol-Myers Squibb, and Boehringer Ingelheim.

Our goal is to improve human health by rapidly discovering, developing and delivering innovative medicines and technologies to all patients. Our success is predicated on attracting and retaining top talent, generating new ideas and promoting an open and collaborative culture.

We embrace diversity across all dimensions and levels of the organization, and we strive to ensure every employee is supported in reaching their full potential. We hire motivated people with diverse backgrounds, identities, experiences and skillsets. We are committed to fostering an inclusive culture where all employees feel valued, respected and empowered to create value for patients.

The Principal, Biostatistician will own the statistical and quantitative work that connects clinical evidence to the most important decisions Roivant makes across its pipeline. This is not a strategy role — this is a figure-things-out and get-things-done role in a high-stakes environment with substantial ownership. We expect you to get to ground truth on the hardest clinical and scientific questions the company faces, working directly in trial datasets and translating rigorous analysis into recommendations that leadership acts on.

The Principal will pressure-test the clinical assumptions underpinning key pipeline and commercial decisions, build the statistical frameworks needed to evaluate evidence across assets, and ensure Roivant has a clear-eyed view of what its data shows. The scope is intentionally broad and is well-suited to a high-potential individual earlier in their career with exceptional upside and a strong desire to take on responsibility.

• Work directly in ongoing and completed clinical trial datasets (CSRs, patient-level data, interim readouts) to identify efficacy signals, safety patterns, and subgroup effects that inform go/no-go and commercialization decisions
• Build rigorous statistical analyses from scratch: mixed-effects models, longitudinal models, Bayesian frameworks, subgroup analyses, and sensitivity analyses across Roivant's pipeline assets
• Monitor emerging safety signals and unexpected findings in real time across ongoing studies; surface and contextualize them for leadership before they become surprises
• Pressure-test clinical assumptions: challenge endpoint choices, scrutinize statistical analysis plans, and flag where the data does not support the narrative
• Execute focused 1-5 day analytical sprints on the highest-priority questions from Roivant and Vant leadership
• Develop a deep, differentiated read of the clinical evidence base for Roivant's near-commercial assets: what the data shows, what it does not, and where the science is genuinely uncertain
• Analyze competitors' trial data, published and unpublished, with the same rigor applied to Roivant's own: endpoints, patient populations, effect sizes, and durability
• Synthesize findings from literature, registries, claims, and proprietary datasets into…