BridgeBio Pharma
biopharma
AssociateDirector,Biostatistics&AI
Neural analysis suggests this role is
optimal for Director candidates.
“Associate Director, Biostatistics & AI at BridgeBio Pharma. Skills: Biostatistics, AI/ML engineering, LLM-powered tools, RAG pipelines, statistical concepts. ethical support responses to health authority queries. Stay current with FDA, EMA, and ICH guidance on statistical methodology, and real-world evidence (RWE)”
What You'll Achieve.
develop life-changing medicines for patients with unmet needs as fast as humanly possible
Industry & Context.
empower people to solve problems
What They're Looking For.
Must Have
3+ years of hands-on AI/ML engineering experience, Python proficiency for AI/ML, Foundational understanding of statistical concepts (e.g., hypothesis testing, regression, survival analysis) relevant to clinical development, Knowledge of statistical methodologies, current drug development trends, and regulatory environments (FDA, EMA, ICH), Excellent written and verbal communication skills, Ability to work as part of a cross-functional team in a fast-paced environment
Nice to Have
AI Interface Setup working knowledge of Python for data science or scripting, Demonstrated exposure to AI/ML tools — such as LLM APIs, prompt engineering, or automation scripting — with a interest in expanding these capabilities in a GxP environment, Deep knowledge of CDISC standards (SDTM, ADaM, Define-XML) and regulatory submission experience contributing to NDALA/MAA preferred, working familiarity with SAS and/or R in a statistical or data science context, Meaningful exposure to clinical or life sciences data — e. g. , working with clinical trial datasets, CDISC standards, pharmacovigilance data, or regulated environments (GxP/21 CFR Part 11) — with eagerness to deepen this domain expertise, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, dbt Certified
What You'll Do.
ethical support responses to health authority queries
Stay current with FDA
and ICH guidance on statistical methodology
and real-world evidence (RWE)
building and deploying LLM-powered tools
RAG pipelines (LangChain or equivalent)
and/or MLOps infrastructure
How You'll Work.
Team & Collaboration
work alongside some of the most respected minds in the industry; work as part of a cross-functional team; collaborate effectively with external partners and vendors
Communication Scope
Excellent written and verbal communication skills; ability to engage both technical and non-technical audiences
Full Job Description
Mavericks Wanted When was the last time you achieved the impossible? If that thought feels overwhelming, you might want to pause here, but if it sparks excitement...read on In 2015, we pioneered a “moneyball for biotech” approach, pooling projects and promising early-stage research from academia together under one financial umbrella to reduce risk and unleash innovation. This model allows science and small teams of experts to lead the way. We build bridges to groundbreaking advancements in rare disease, and develop life-changing medicines for patients with unmet needs as fast as humanly possible. Together we define white space, push boundaries, and empower people to solve problems. If you're someone who defies convention, join us and work alongside some of the most respected minds in the industry. Together, we'll ask "why not?" and help reengineer the future of biopharma. At BridgeBio, we value curiosity and experimentation—including the ethical support responses to health authority queries • Stay current with FDA, EMA, and ICH guidance on statistical methodology, and real-world evidence (RWE) AI Interface Setup working knowledge of Python for data science or scripting Demonstrated exposure to AI/ML tools — such as LLM APIs, prompt engineering, or automation scripting — with a strong interest in expanding these capabilities in a GxP environment Deep knowledge of CDISC standards (SDTM, ADaM, Define-XML) and regulatory submission workflows; experience contributing to NDA/BLA/MAA preferred Track B — AI/ML-First with Pharma/Biostats Exposure 3+ years of hands-on AI/ML engineering experience, including building and deploying LLM-powered tools, RAG pipelines (LangChain or equivalent), agentic workflows, and/or MLOps infrastructure Strong Python proficiency for AI/ML development; working familiarity with SAS and/or R in a statistical or data science context Meaningful exposure to clinical or life sciences data — e.g., working with clinical trial datasets, CDISC standa
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