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Principal Data Scientist (AI)

204 500 - 267 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Релокация
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Principal Data Scientist (AI): Developing advanced models for patient selection, therapeutic hypothesis evaluation, biomarker identification, and clinical trial optimization with an accent on computational biology, multimodal bioinformatics, and machine learning. Focus on building AI agents for biomedical workflows, translating complex biological data into actionable insights, and presenting analytical findings to senior stakeholders.

Location: Hybrid, requiring 3 days per week in office in the New York City or Boston metro areas. Applicants from the Research Triangle, NC, and San Francisco Bay Area may also be considered. Candidates must reside in these locations or be willing to relocate.

Total compensation: $204,500–$267,000 per year, plus equity, comprehensive benefits, and perks.

Company

hirify.global is a technology and AI-driven pharmaceutical company developing platforms and capabilities to accelerate drug development and clinical trials.

What you will do

  • Lead complex data science projects that advance the drug development portfolio.
  • Develop models for therapeutic hypothesis evaluation, patient stratification, and biomarker identification.
  • Design AI models for modernizing clinical trial evaluations, including surrogate endpoints.
  • Help develop and train AI agents that automate and optimize biomedical workflows.
  • Collaborate with clinical, technical, and research teams.
  • Present complex analytical findings to senior stakeholders and executive leadership.

Requirements

  • PhD in computational sciences or life sciences.
  • 5+ years of post-academic experience in life sciences, biotech, pharma, or consulting.
  • Strong programming skills, particularly in Python.
  • Extensive experience with multimodal bioinformatics analysis.
  • Ability to work in a hybrid arrangement with regular office attendance in the listed U.S. hubs.

Nice to have

  • Experience with cloud computing environments and tabular or graph databases.
  • Strong background in machine learning and deep learning for biological applications.
  • Experience with large language models.
  • Experience collaborating with engineering teams on production systems.
  • Strong communication skills and experience presenting technical findings to senior stakeholders.

Culture & Benefits

  • Work on AI-driven pharmaceutical development intended to bring new medicines to patients faster.
  • Equity in addition to base compensation.
  • Comprehensive benefits and generous perks.
  • Inclusive, equal-opportunity workplace.

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