5 дней назад
Solutions Engineer, Life Sciences
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Solutions Engineer, Life Sciences (AI/Data Science): Designing product demonstrations, proof-of-concepts, and technical architectures for life sciences organizations with an accent on drug discovery, clinical analytics, regulated workflows, and scientific computing platforms. Focus on building Python or R prototypes, addressing data governance and reproducibility requirements, and guiding customer engagements toward production deployments.
Location: Remote US (East Coast)
Company
AI and data science software platform providing model development, MLOps, collaboration, reproducibility, and compliance capabilities for large organizations.
What you will do
- Understand customer workflows, technical constraints, and problems, then shape suitable platform solutions.
- Design and run hands-on proof-of-concept projects for drug discovery, clinical analytics, regulatory submissions, and omics data processing.
- Partner with account executives to design architectures addressing data governance, reproducibility, validation, 21 CFR Part 11, and GxP requirements.
- Identify additional life sciences use cases and build reusable technical environments and engagement assets.
- Build custom prototypes and applications on the platform using AI-assisted coding tools.
- Work with Customer Success and Solutions Architects to transition successful proof-of-concepts into production deployments.
Requirements
- Technical background in life sciences, technology, software, solutions engineering, consulting, or an equivalent customer-facing technical environment.
- Working knowledge of at least one life sciences domain, such as drug discovery, clinical development, computational biology, manufacturing/QC, or regulatory data management.
- Experience owning or contributing to an internal platform or shared scientific computing environment.
- Experience with technical evaluations, pilots, proof-of-concepts, or comparable solution-diagnosis work.
- Production or near-production coding experience, including internal tools, pipelines, or applications for scientific teams.
- Proficiency in Python and/or R, plus hands-on experience with data science and ML tools used in life sciences.
Nice to have
- Experience building, validating, and moving models toward production in a regulated context.
- Experience with 21 CFR Part 11 or GxP environments.
Culture & Benefits
- Startup-oriented environment within a company backed by leading technology and investment partners.
- Commitment to diversity, inclusion, and respectful collaboration.
- Growth mindset with an emphasis on continuous improvement.
- Teaching and learning environment designed to support success in the role and across the company.
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