Senior Scientist II, Computational Biology, Pharma R&D

Location: Boston, United States

Salary: $100,000–$160,000 for Chicago and $115,000–$175,000 for New York City; ranges may vary by location.

Company

hirify.global develops an AI-powered precision medicine platform connecting real-world evidence with clinical insights and treatment decisions.

What you will do

• Partner with pharmaceutical collaborators on target discovery, biomarker development, clinical development, and drug modality programs.
• Design and execute reproducible analyses integrating genomic, transcriptomic, imaging, and clinical datasets.
• Apply statistical and computational methods to clinical trial design, patient selection, treatment response, resistance mechanisms, and disease biology.
• Develop LLM- and agentic workflows that accelerate coding, discovery, documentation, review, and predictive modeling.
• Develop reusable methods, internal packages, scalable solutions, and software engineering best practices.
• Lead projects, mentor junior scientists, communicate findings, and prepare reports, partner deliverables, manuscripts, and conference materials.

Requirements

• PhD in Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or a related field, or a master’s degree with 4+ years of relevant experience, plus 2+ years of industry or postdoctoral experience.
• Proficiency in R and/or Python, scientific computing libraries, machine learning, LLM-based coding assistants, and agentic frameworks.
• Strong grounding in statistics, data analysis, study design, real-world clinical data interpretation, version control, modular coding, documentation, and code review.
• Experience analyzing large-scale biological datasets such as NGS, RNA-seq, genomics, or transcriptomics data.
• Strong understanding of cancer biology, immunology, or human disease mechanisms, with peer-reviewed publications or equivalent scientific achievements.
• Demonstrated project leadership, mentorship, communication skills, and comfort in client-facing collaboration.

Nice to have

• Experience configuring or adapting generative AI and LLM tools for scientific work.
• Expertise in real-world evidence, survival analysis, causal inference, network or systems biology, or multimodal integration.
• Understanding of the drug development lifecycle from target discovery through clinical development.
• Experience with SQL and large relational databases.

Culture & Benefits

• Cross-functional collaboration across Research, Clinical, Data Science, and Engineering.
• Work focused on precision medicine, healthcare innovation, and pharmaceutical research partnerships.
• Benefits may include incentive compensation, restricted stock units, medical coverage, and other benefits depending on the position.