Contractor Medical Analytics, Evidence Generation; AD

Position: Contractor Medical Analytics, Evidence Generation (AD)
Employment as a Contingent Worker aligns well with individuals seeking career flexibility and non-traditional work arrangements, while also being motivated to produce exceptional results in prominent roles. Magnit Direct Source is a service provided by Magnit Global that connects top-tier talent directly to an industry-leading company. Daiichi Sankyo, Inc. and Magnit Global, in collaboration, offer flexible contingent assignments across diverse projects creating opportunities for engaging work. 

As a Contingent Worker, you will not be employed Daiichi Sankyo, Inc. You will be employed by our Managed Service Provider, Magnit Global, which oversees the majority of our temporary contract recruitment. Contractor Medical Analytics, Evidence Generation (AD) The Contractor, Medical Analytics, Evidence Generation will partner with Global and regional Medical Affairs, R&D, Technology Operations, IT, Change Enablement, and Evidence planning subject matter experts to design, implement, and advance end to end analytical solutions that support evidence planning.

This role owns the analytical framing, methods, metrics, interpretation, validation, and decision support for Evidence Generation digital capabilities. The role will help connect strategic imperatives to evidence gaps, study concepts, studies, and study status, and use these insights to support decision making and assess impact from evidence generation activities.

Work Location:

Candidate can work 100% remote for duration of the assignment Ability to travel up to 10% (mostly to Basking Ridge, NJ). Responsibilities:
Analytical Discovery and Requirements Definition Translate evidence planning needs into analytical solutions by working with GOMA, regional Medical Affairs, R&D, and evidence planning SMEs to define business questions, workflows, data requirements, and what good looks like for evidence planning decision support. Lead analytical working sessions with evidence planning SMEs and cross-functional partners to define analytical questions, data needs, metric logic, decision criteria and data-quality requirements for Evidence Generation dashboards and data products.

Lead the analytical assessment of the current IEP dashboard and define the analytical framework and requirements for enhanced evidence planning capability that maps strategic imperatives to evidence gaps, study concepts, studies, and study status, including planned, ongoing, completed, and published studies. Assess and recommend potential AI/advanced analytics use cases based on feasibility, data availability, expected value and limitations, in partnership with the Technology Implementation and IT teams.

Analytical Design and Data Foundation Develop analytical specifications and acceptance criteria for Evidence Generation dashboards and data products, including the analytical data model, required data elements, metric calculations, analytical business rules, data-quality expectations, analytical views, and documented assumptions. Partner with business leads and the Technology Implementation team to establish common definitions, taxonomies, metadata, status conventions, data ownership, refresh requirements, and data quality expectations needed to implement the analytical specifications and support scalable evidence planning.

Define analytical requirements for integrating Evidence Generation data into the Medical Data Foundation, including data source needs, metric continuity and analytical data quality, enabling Technology Implementation and IT teams to create the core and analytical data pipeline needed for the final visualization. Insights and Evidence activity Impact Measurement Generate actionable insights from dashboard outputs to help stakeholders identify evidence…