AstraZeneca
Healthcare
SeniorAnalyst-MedicalDataOffice
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Analyst - Medical Data Office at AstraZeneca. Skills: Data Analytics, Business Intelligence, Data Modelling, Reporting. Design custom reports. Run standard reports”
What You'll Achieve.
Increase consistency; Operate more efficiently; Ensure scalability; Ensure performance; Ensure maintainability; Maintain single source of truth; Elevate reporting maturity; Elevate platform maturity; Elevate metric maturity; Ensure accuracy; Ensure integrity; Ensure reliable refreshes
Industry & Context.
Investigate data issues; Reconcile discrepancies; Produce actionable recommendations
What They're Looking For.
Must Have
Quantitative bachelor’s degree, 5+ years of experience, Proficient with Power BI, Proficient with Excel/Power Query, Solid understanding of Python, Good understanding of data quality practices, Demonstrated ability to investigate data issues, Demonstrated ability to reconcile discrepancies, Demonstrated ability to produce actionable recommendations
Nice to Have
Experience with Databricks, Experience with AWS S3/Redshift, Experience with Power Apps, Experience building data models, Familiarity with data pipelines, Familiarity with scheduling for automated refresh, Understanding of Medical/Scientific data domains, Familiarity with Veeva/Medical platforms, Familiarity with enterprise data hubs, Exposure to metric standardisation, Exposure to taxonomy/ontology usage, Exposure to semantic models, Experience partnering with multiple collaborators, Comfort with compliance-aware analytics practices
What You'll Do.
Design custom reports
Perform rapid ad hoc analyses
Create reusable data models
Develop Power BI dashboards
Automate capture of datasets
Automate integration of datasets
Own transformation choices
Own calculation choices
Safeguard global data integrity
Drive consistent surface issues
Coordinate resolution with partner teams
Identify datasets to validate business rules
Source datasets to validate business rules
Resolve conflicts within systems
Resolve conflicts across systems
Identify requirements
Propose new capabilities
Support Medical platforms
Support data products
Partner with Medical teams
Partner with multi-functional teams
Embed data-driven decision-making
How You'll Work.
Team & Collaboration
Cross-functional teams; Medical teams; Multi-functional teams; Partner teams
Communication Scope
Translate Medical needs; Deliver concise insights
Process & Methodology
Agile
Full Job Description
## **Job Title: Senior Analyst - Medical Data Office** ## **Career Level: D1** ## **Introduction to role:** Are you ready to turn complex Medical data into decisions that reach patients faster? In this role, you will transform fragmented datasets into trusted insight products that Medical leaders use to act with confidence. Your work will give clarity to urgent questions, standardize critical metrics, and build the analytics backbone that powers better outcomes. You will join a fast-moving, collaborative team focused on becoming a tech-enabled enterprise. By driving automation, crafting scalable data models, and crafting interactive Power BI reports, you will remove friction and increase consistency. You will also help the organization operate more efficiently. Will you take ownership of the data designs and dashboards that leaders rely on every week to guide strategy? ## **Accountabilities:** * Medical Reporting and Analytics: Design and run custom and standard reports using Excel, Power Query, SQL/Python; perform rapid ad hoc analyses that answer urgent Medical questions and inform timely decisions. * Create robust and reusable data models across various sources. Develop intuitive Power BI dashboards with DAX that align to standard Medical benchmarks. This allows consistent performance tracking. * Automation and Ingestion: Automate the capture and integration of manual and external datasets outside core hubs to create repeatable, low-touch reporting and analytics pipelines. * Data Design and Decisions: Own schema, transformation, and calculation choices to ensure scalability, performance, and maintainability as demand and data volumes grow. * Data Quality and Consistency: Proactively monitor data quality, safeguard global data integrity, and drive consistent reporting; surface issues early and coordinate resolution with partner teams. * Rules Validation and Conflict Resolution: Identify and source datasets to validate business rules and requirements; resolve confl
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