About the role
We are seeking a Data Analysis Project Manager to act as the primary quality gatekeeper
during this critical migration phase.
focusing on the platform's data analysis capabilities.
whether the results genuinely meet the agreed-upon DoR criteria, and filter them before
passing complex issues to internal Data Analysis Subject Matter Experts (SMEs).
outstanding readiness gaps.
and internal scientific stakeholders to clarify testing requirements and resolve technical
blockers.
readiness meetings, ensuring business requirements are strictly met.
understand, evaluate, and challenge the analytical test outputs provided by the technical
execution team.
tracking multiple DoR criteria, test statuses, and follow-ups systematically. Ability to
manage conflicting priorities effectively.
technical and non-technical stakeholders to explain DoR impacts and timelines). Must be
highly resilient, comfortable holding delivery teams accountable to strict criteria, and
capable of maintaining a firm stance on quality without compromising.
We reserve the right to contact the selected candidates.
Do you fit?
Technical Literacy: Strong foundation in Python and Cloud platforms to effectively understand, evaluate, and challenge the analytical test outputs provided by the technical execution team.
Project Management & Governance: Organized and process-driven, capable of tracking multiple DoR criteria, test statuses, and follow-ups systematically. Ability to manage conflicting priorities effectively.
Stakeholder Management: Strong communication skills (e.g., clear communication with technical and non-technical stakeholders to explain DoR impacts and timelines). Must be highly resilient, comfortable holding delivery teams accountable to strict criteria, and capable of maintaining a firm stance…
What you'll own
Oversee Readiness Execution: Manage and govern the DoR testing cycle, specifically focusing on the platform's data analysis capabilities.
Evaluate & Validate: Collect test outputs from the platform delivery team, evaluate whether the results genuinely meet the agreed-upon DoR criteria, and filter them before passing complex issues to internal Data Analysis Subject Matter Experts (SMEs).
Track Progress: Maintain clear visibility on testing execution, success rates, and outstanding readiness gaps.
Bridge Communication: Act as the central liaison between the platform delivery team and internal scientific stakeholders to clarify testing requirements and resolve technical blockers.
Quality Representation: Act as the formal representative for platform quality in all readiness meetings, ensuring business requirements are strictly met.
Benefits & perks
Sound like you?
Negotiable · Transition Technologies MS
On Transition Technologies MS's website · ~2 minutes
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