New York, NY
AI-native pharma company accelerating drug development
Formation Bio is an AI-native pharma company that acquires clinical-stage drugs from pharma, universities, and biotech firms. It develops them faster and more efficiently using proprietary tech-driven platforms focused on clinical trials, data science, and AI models. This approach addresses inefficiencies in traditional drug development to bring new treatments to patients sooner.
Lead technical recruiting for data science, engineering, and product teams at an AI-native pharma company. Own end-to-end hiring for technical roles, partner strategically with leadership, and leverage AI tools to optimize sourcing, evaluation, and process efficiency while maintaining a high bar for talent.
The Associate Director, GMP Quality Assurance ensures compliance for Formation Bio's biologics portfolio by reviewing GMP documents, conducting batch releases, leading investigations, auditing CDMOs, and supporting regulatory inspections. Requires 10+ years GMP QA experience in large-molecule manufacturing, bachelor's in a scientific field, and hands-on quality leadership in a dynamic environment.
Lead drug asset development as accountable General Manager, owning strategy, P&L, execution, and cross-functional coordination to drive value inflection with speed and AI leverage.
Lead external brand and media relations for an AI-driven pharma company. Own PR strategy, journalist relationships, executive positioning, and brand initiatives while building AI-powered communications systems.
Lead quality strategy for drug development assets at an AI-native biotech. Embed QbD, manage risk frameworks, conduct due diligence, and ensure audit readiness from preclinical through commercialization.
Translate AI-driven drug development predictions into measurable portfolio outcomes by building portfolio construction, risk monitoring, and performance attribution systems. Requires 1-3 years quantitative experience, strong Python skills, and portfolio construction fundamentals.
Lead RWD strategy and data engineering at a tech-driven pharma company. Own sourcing, harmonization (OMOP), infrastructure, and vendor management to deliver analysis-ready datasets supporting drug development and portfolio decisions.
Lead product strategy and AI-driven solutions for major drug development domains like clinical trials and regulatory submissions. Own outcomes for cross-functional teams of engineers, data scientists, and PMs while embedding with clinical and regulatory leaders.
Senior Data Engineer building scalable pipelines to transform EHR and claims data into analytics-ready assets while conducting hands-on real-world evidence analyses. Requires 5+ years experience with 2+ years in healthcare data, strong SQL/Python, Snowflake/dbt/Dagster, and familiarity with OMOP and causal inference frameworks.
Lead data science initiatives at a tech-driven pharma company to accelerate drug development using AI models for patient stratification, biomarker discovery, and clinical trial optimization. Requires a PhD and 7+ years experience in life sciences with strong Python and bioinformatics skills.
Software Engineer building production systems at an AI-native pharma company to accelerate drug development across clinical, regulatory, and operations domains.
Lead development of deep learning models for medical imaging analysis to accelerate drug development and clinical trials. Requires PhD with 5+ years building production AI models for MRI/X-ray analysis.
Lead AI and data science initiatives to advance drug development, focusing on patient stratification, biomarker identification, clinical trial optimization, and AI agent development for biomedical workflows. Requires PhD and 5+ years experience in life sciences with strong Python and bioinformatics skills.
Lead business development efforts to identify, evaluate, and source early-stage biotech and pharmaceutical assets for tech-enabled drug development. Requires strong scientific background (PhD/MD preferred) plus 3-7 years experience in BD, VC, or consulting.
Lead development of deep learning models for medical image analysis (MRI, X-ray) to accelerate clinical trials, create AI biomarkers, and integrate imaging AI into drug development workflows. Requires PhD and 5+ years building production-grade medical imaging AI.
Lead AI-driven data science initiatives for drug development, building models for patient stratification, biomarker identification, and clinical trial optimization. Requires a PhD and 3+ years post-academic experience in life sciences with strong Python and bioinformatics skills.