Scientific Project Manager

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.

• 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.

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.

• 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.
• 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.
• 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 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 (e.g., data science, computer science, statistics, mathematics, or engineering) is desirable.

3‑5 years of relevant project management experience. Preferred:
Project Management Professional (PMP) or similar certification. Technical degree (bachelor’s or higher) in a quantitative discipline.

• PMP or other professional project management certifications.
• Strong scientific or technical domain expertise in data science, analytics, or a closely related field.

On site in LC.

This role will require interfacing with scientists across multiple domains, so the candidate must be comfortable working cross-functionally.

Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of
• Minority / Gender / Disability / Religion / LGBTQI / Age / Veterans.