• Act as the primary liaison between Product Analytics and Data/BI teams, aligning on data needs and priorities. • Define data requirements and support event taxonomy design. • Ensure data quality, consistency, and governance standards across datasets. • Support scalable reporting and dataset optimization aligned with enterprise data strategy. • Define and oversee experimentation standards, ensuring statistical validity and consistency. • Review experiment results and analytical outputs to ensure quality and accuracy. • Coach analysts on statistical thinking and analytical frameworks. • Drive continuous improvement of experimentation practices across teams. • Mentor and support Product Analytics Analysts in their technical and professional growth. • Support product roadmap prioritization through data-driven insights. • Translate complex analyses into clear, strategic recommendations. • Present insights to senior stakeholders and leadership.

• You apply VIDA’s spatial analysis tools and prepare our software for real-life projects - these can range from energy access planning to agriculture or climate risk assessment. • You improve, automate, and extend our workflows with Python and SQL scripting. • You explore, pre-process and integrate new datasets and map layers into the VIDA software. • You explore and implement new spatial data analysis methods, for example by using Machine Learning methods and sector-specific modelling frameworks. • You ensure clear documentation, reporting, and communication across all project phases. • You ensure project outputs (VIDA software products and reports) meet technical quality standards and are accessible to end-users. • You interact with our international project partners and clients, and prepare/present your work in reports and presentations, both in English and French. • You facilitate workshops, trainings, and meetings to ensure alignment and adoption of project outcomes, both in English and French.

• Plan and perform care gap advanced analytics and segment HCPs and KOLs using real world data sources as input • Support team Product Manager in strategic and tactical planning with regards to medical analyses • Collaborate with team Product manager to communicate generated insights • Provide mentorship & coaching to Data Scientists & Data Engineering • Leverage cross-team collaboration to develop analytical best-practices in care gap analyses and HCP segmentation • Proactively identify future opportunities to enhance the impact of care gap and segmentation solutions • Prepare and maintain datasets for high-complexity analytical needs • Own the end-to-end process of integrated care gaps analyses • Plan, generate and perform asset-specific care gap analyses • Create asset-specific HCP segments to guide medical activities

• Configure/maintain EDC forms and eCRF specifications as needed to support ingestion and downstream analysis, focusing on scalability and standardization. • Own end-to-end Data Management for Evidence Generation studies: build, validate, and maintain research databases from ingest → cleaning → QC → data lock. • Develop and run data cleaning workflows (queries, reconciliation, audit trails), and ensure inspection-ready documentation. • Design and operate data model strategy for automated ingestion of EHR-level RWE into the EDC. • Work hands-on with APIs/integration endpoints and unify disparate data models (site/EHR variability, mapping logic, versioning, schema evolution). • Partner with site IT/informatics and the Product team to understand EHR constraints, extract structures, and change management. • Translate EHR data realities into feasible study data capture and monitoring plans. • Create and maintain DMPs, SAPs, SOPs, runbooks, and training materials that operationalize the above processes across care pathways. • Perform statistical analyses on cleaned datasets (descriptive, comparative, time-to-event where appropriate) and support evidence packages and reporting.