Scientific Project Manager, Quantitative Insights

• Real world data
  , data about clinical trial.
• Organizing workshop, brainstorming sessions
  .
• Developing AI methodology for patient trial.
• Project tracking tool for resourcing
• Run Agile
  , Agile framework in scientific environment is MUST
• MS team, SharePoint, Smartsheet for tracking
• Good to have 5 days onsite , can be hybrid tues-thurs.
• Experience is more important the PMP certification.
• BS/MS degree, 3-5 years experience
• All internal communication primarily.
• Even IT PM with Agile framework
• R&D, bioinformatics group.

The Scientific Project Manager
, QuIL will be responsible for the effective management of data-driven and analytics projects within QuIL, an agile, projectized organization.

This role involves working closely with the Chief of Staff for QM&G and the Head of QuIL to implement the operating model, support resource planning, coordinate workshop logistics
, and lead sprint management activities.

The project manager will ensure stakeholders have transparent access to project and sprint status by establishing the right tools and processes.

• The ideal candidate will have a strong background in project management within technical or data science domains and experience managing complex projects with multiple stakeholders.
• Excellent communication and organizational skills are required.
• Familiarity with agile methodologies, data science, analytics, or related technical fields is desirable but not necessary.
• Experience with implementing project management tools and continuous improvement practices is a plus.
• Relevant project management certifications or a technical degree at the bachelor's or higher level are advantageous.
• This is an individual contributor role requiring the ability to work cross-functionally in a dynamic and iterative environment.

• Coordinating project activities and timelines across multiple concurrent data science projects and sprints.
• Facilitating team communication and fostering collaboration between QuIL scientists, visiting scientists and cross-functional partners.
• Organizing and supporting logistics for agile sprints, workshops, and resource planning sessions.
• Implementing tools and processes for tracking sprint progress, managing deliverables, and facilitating knowledge transfer within the team.
• Proactively identifying and driving operational efficiencies to optimize the QuIL team's effectiveness.

• Project management: Strong knowledge and experience in project management methodologies (especially Agile), tools, and techniques.
  Prior experience managing data science, analytics, or cross-functional technical projects. Ability to introduce structure and organization into dynamic, fast-paced environments.
• Communication: Excellent communication and interpersonal skills to facilitate discussions, coordinate with multiple technical and non-technical stakeholders, and drive effective collaboration across data science and business functions.
• Organization: Exceptional organizational skills to manage parallel initiatives, prioritize deliverables, and maintain meticulous attention to detail. Ability to efficiently coordinate complex, cross-functional data projects and sprints.
• Efficiency: Proficiency in managing sprint timelines, tracking progress toward deliverables, and driving accountability. Proactively identify, communicate, and help resolve project risks or blockers to ensure continuous delivery.
• Foundational scientific or technical domain expertise: Foundational knowledge in data science, analytics, or a closely related technical domain. Proven ability to work with data scientists, analysts, and technical stakeholders. A background in a quantitative field (such as data science, computer science, statistics, mathematics, or engineering) is desirable.
• Certifications: Professional certifications in project management such as PMP (Project Management Professional) could demonstrate a strong foundation in project management principles.
• This role will require interfacing with scientists across multiple domains, so the candidate must be comfortable working cross-functionally.

• 3-5 years

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