AstraZeneca

Healthcare

SeniorAnalyst-MedicalDataOffice

₹19–28L ~AI est. India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“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.

Healthcare
Problems you'll solve

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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