Senior Product Manager, AI-Driven Clinical Trials

Amazon Web Services (AWS)

Seattle (WA)

On-site

USD 151,000 - 205,000

Full time

14 days+
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Benefits offered by this job

Health insurance
401(k) matching
Paid time off
Parental leave
Flexible Spending Accounts

Job summary

Amazon Development Center U.S., Inc. seeks a Senior Product Manager to lead AI-driven clinical trials initiatives.

You will oversee a team of product managers, developers, and scientists to define novel, generative AI experiences for pharmaceutical and biotech clients, guiding transformation of clinical evidence and trial operations. You will shape product direction, evaluate machine learning approaches, and reimagine user workflows to replace fragmented processes with learning systems at global

Qualifications

  • Bachelor's degree required.
  • Experience owning/driving roadmap strategy and definition.
  • Experience with feature delivery and tradeoffs of a product.
  • Experience contributing to engineering discussions around technology decisions and strategy for a product.
  • Experience managing technical products or online services.

Responsibilities

  • Lead pioneering product development for AI-driven clinical trials transformation.
  • Guide a team of product managers, developers, and scientists to define novel experiences.
  • Invent and simplify for pharmaceutical companies, biotech firms, and clinical operations teams.
  • Reimagine workflows, adopting new ML techniques and improving trial operations.

Skills

Roadmap strategy
Product delivery
Engineering discussions
Stakeholder management

Education

Bachelor's degree

Tools

Tableau
QlikView
QuickSight

Job description

Amazon Development Center U.S., Inc. seeks a Senior Product Manager to lead AI-driven clinical trials initiatives.

You will oversee a team of product managers, developers, and scientists to define novel, generative AI experiences for pharmaceutical and biotech clients, guiding transformation of clinical evidence and trial operations. You will shape product direction, evaluate machine learning approaches, and reimagine user workflows to replace fragmented processes with learning systems at global

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