AstraZeneca
Chennai, Tamil Nadu, India Posted 5d ago
At AstraZeneca, you will be a hands-on internal consultant to a specific brand team, ensuring the data that fuels our commercial analytics is accurate, consistent and fit for purpose. You will connect thorough data quality practices with advanced analytics to help shape strategy across segmentation and targeting, patient opportunity identification, return on investment analyses, and market simulations.
Key Responsibilities
Data Quality Strategy and Governance: Define, implement and continuously improve data quality frameworks, standards and controls that ensure accuracy, completeness and timeliness of syndicated, custom and longitudinal datasets used for brand analytics.
Analytical Solution Design: Design, build and validate predictive and prescriptive analytical solutions that enable brand teams to make evidence-based decisions, ensuring data lineage, reproducibility and model transparency throughout.
Longitudinal Data Stewardship: Lead the integration, harmonization and quality assurance of claims, EMR and other patient-level data to unlock reliable insights across patient journeys and market dynamics.
Segmentation and Targeting Excellence: Develop and operationalize high-quality customer segmentation and targeting approaches, linking data quality checks directly to downstream field effectiveness and resource allocation.
Measurement and return on investment analytics: Drive robust test-and-learn designs, return on investment analyses and performance measurement, embedding controls to reduce bias and increase confidence in outcomes.
Market Simulation and Patient Flow Modelling: Translate data into actionable simulations and patient flow models, ensuring inputs and assumptions meet defined quality thresholds to inform brand and access strategies.
Collaboration and Influence: Partner with cross-functional leaders to identify business questions, prioritize enhancements, and embed new analytic capabilities and quality practices across teams.
Capability Development: Champion modern platforms and methods, mentor colleagues in advanced analytics and data engineering guidelines, and cultivate a culture of continuous improvement and curiosity.
Requirements
Quantitative Bachelor's degree or equivalent experience in Engineering, Operations Research, Management Science, Economics, Statistics, Applied Math, Computer Science or Data Science.
2+ years of experience in Pharmaceutical / Biotech / Healthcare analytics or secondary data analysis.
5+ years of experience in application of advanced methods and statistical procedures on large and disparate datasets.
4+ years of recent experience and proficiency with PySpark, Python, R, SQL.
Working knowledge on platforms like Databricks.
Experience in MS Office products - Excel and PowerPoint skills required.
Proficiency in manipulating and extracting insights from large longitudinal data sources, such as Claims, EMR and other patient level data sets.
Preferred Qualifications
Experience with IQVIA data sets.
Statistical analysis and modelling background.
