• Desenvolver dashboards e soluções analíticas em Power BI • Estruturar modelos de dados eficientes e escaláveis • Criar métricas e indicadores utilizando DAX • Realizar tratamento e transformação de dados com Power Query • Trabalhar com consultas e organização de dados em SQL e Snowflake • Apoiar análises e automações utilizando Python • Interagir com áreas de negócio para entendimento e refinamento das demandas • Garantir qualidade, performance e clareza das entregas analíticas

• Serve as a member of the project team with primary responsibility for coordinating the clinical data review, query generation / resolution and reconciliation activities to support the Data Management lead with the delivery of clinical data according to client quality and integrity specifications, project timelines and productivity targets. • Assist in the development of the project Data Management Plan, including data review guidelines /diagnostics specification and setup of the data management systems according to project requirements. • Serve as back-up to Clinical Data Manager, with oversight of data management activities for the delivery of clinical data according to client quality and integrity specifications, project timelines and budgets. • Ensure that all allocated projects are carried out in strict accordance with the relevant protocols, global harmonized SOPs, and the specified standards of GCPs. • Perform all data management tasks as appropriate to include, but not to be limited to data review and query management to ensure that quality standards (both internal and client) are achieved within stipulated timelines. • Assist with reviewing clinical trial data in accordance with Data Management Plans, Edit Check Specifications and/or Data Review Guidelines and raise queries to resolve erroneous, missing, incomplete data. • Generate, resolve and track queries to address problematic data identified during aggregate data review activities. • Run and execute additional programs, special listings, reconciliation discrepancy listings etc.) used to support the review of clinical trial data. • Interact with other project team members to support the set-up, maintenance, and closure of the Data Management aspects of the project and attend meetings as required. • Assist with review of data listings for internal data review. • Assist or create dummy data to test edit checks and to test database screen design and functionality. • Assist or create dummy data to test SAS reports and data listing. • Modify standard templates to create study specific Data Management Plans, or eCRF completion guidelines. • Support team members by creating forms/memos as required. • Posting of Data Management documentation and data management related administrative tasks as requested, including maintenance of eTMF as required. • Generate study status reports. • Perform database extracts. • Assist with the completion of Database Lock activities. • Support the training of new staff on project specific Data Management processes.

• Design and deliver tailored data insights that translate clinical and quality information into clear, actionable recommendations for customers • Build and apply statistical and predictive models to identify patterns, trends, and opportunities for performance improvement • Apply clinical data expertise to evaluate quality outcomes and measure the impact of improvement initiatives • Contribute analytical input to cross-functional initiatives supporting service and process improvement • Support the design, development, and testing of business intelligence reporting and analytics solutions • Engage in collaborative working groups to define data processing and visualisation requirements with internal teams and external partners • Partner with commercial and technical teams, including Sales, Marketing, Research and Development, Implementation, and Support, to support evidence generation, lifecycle data collection, and ROI analysis • Identify opportunities to enhance customer value through data-led insights that support retention and growth

• Build the reconciliation foundation. Design and implement the data infrastructure that reconciles transactions across internal systems (e.g., operation, ledger) and external partners (ACH networks, banking rails, payment processors), ensuring every dollar in equals every dollar out. • Lead anomaly detection and rules development. Develop and maintain a library of anomaly detection rules — covering timing differences, partial matches, unexpected delays, and true errors — and evolve them over time using ML-based signals as data matures. • Implement AI-powered matching. Apply probabilistic and fuzzy matching techniques to automatically resolve ambiguous or near-match transactions, reducing manual review queues and improving straight-through processing rates. • Flag and triage unmatched records. Build real-time and batch pipelines that surface unmatched, delayed, or anomalous transactions to the right stakeholders, with enough context for fast resolution. • Partner cross-functionally as the technical lead. Serve as the primary data partner for Engineering (system integration and pipeline reliability), Finance/Accounting (period-end close, audit support), and Recon Operations (workflow tooling, exception handling). • Define data quality standards. Establish validation frameworks that distinguish expected timing lags from genuine discrepancies, and document data contracts between upstream systems. • Drive automation and process improvement. Identify and eliminate manual reconciliation workloads through scalable pipelines, alerting systems, and self-serve tooling for operations teams. • Elevate the team. Share reconciliation and data quality best practices, mentor analysts, and help establish this function as a core capability within the Analytics org.