Senior Analyst - Brand Analytics

AstraZeneca; India; Sur place; INR 1 300 000 - 1 800 000; Plein temps

Résumé du poste

AstraZeneca in Chennai seeks a Senior Analyst - Data Quality to partner with brand teams, ensuring accurate, consistent data for analytics and decision-making across segmentation, targeting, and ROI studies.

You will govern data quality, design analytical solutions, and mentor peers while leveraging longitudinal datasets and modern platforms to improve efficiency and insight generation.

Qualifications

• Quantitative Bachelor's degree or equivalent in Engineering, Economics, Statistics, or Data Science.
• 2+ years in Pharma/Biotech/Healthcare analytics or secondary data analysis.
• 5+ years applying advanced methods on large/disparate datasets.
• 4+ years proficiency with PySpark, Python, R, SQL.
• Experience with Databricks and data visualization tools is a plus.
• Excel and PowerPoint skills are required.

Responsabilités

• Define and implement data quality frameworks and controls for syndicated, custom and longitudinal datasets.
• Design, build, and validate predictive and prescriptive analytics with data lineage and reproducibility.
• Lead integration and quality assurance of claims and EMR data for patient journeys and market dynamics.
• Develop high-quality customer segmentation and targeting linked to ROI and field effectiveness.
• Drive test-and-learn designs, ROI analyses, and performance measurement with bias reduction.
• Translate data into actionable simulations and patient-flow models for brand and access strategies.
• Collaborate with cross-functional leaders to identify business questions and embed analytics capabilities.
• Mentor colleagues in analytics and data engineering; foster continuous improvement and curiosity.
• Monitor analytics advances in pharma to pilot relevant techniques and strengthen data quality.
• Uphold ethics and compliance in all data and analytics activities.

Connaissances

PySpark

Python

R

SQL

Statistical methods

Machine Learning

Time Series

Bayesian methods

Formation

Bachelor's degree (quantitative)

Advanced degree preferred (Masters/MBA/PhD)

Outils

Databricks

PowerBI

Tableau

MicroStrategy

Qlikview

D3js

Description du poste

Job Title: Senior Analyst - Data Quality

Career Level: D1

Introduction to role:

Are you ready to turn complex healthcare data into trusted insights that power smarter decisions for brands and, ultimately, better outcomes for patients? In this role 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.

Based in Chennai, you will collaborate with Marketing, Medical, Market Access, Sales, Forecasting and other commercial partners to design and deliver robust analytical solutions. You will set a higher standard on how we source, engineer, validate and interpret syndicated and custom datasets, including longitudinal patient-level data. Do you thrive on building confidence in data so teams can move faster and act with clarity?

Accountabilities:

• 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.
• Innovation and External Scanning: Monitor advances in analytics and data engineering within and beyond pharma, piloting relevant techniques and technologies to strengthen data quality and insight generation.
• Ethics and Compliance: Uphold the highest standards of ethics, compliance and transparency in all data and analytics activities, ensuring responsible use of patient-level and commercial data.

Essential Skills/Experience:

• Quantitative Bachelor's degree or equivalent experience from an accredited college or university is required in one of the following or related fields: Engineering, Operations Research, Management Science, Economics, Statistics, Applied Math, Computer Science or Data Science. An advanced degree is preferred (Master's, MBA or PhD).
• 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.
• Working knowledge of data visualization - PowerBI, MicroStrategy, Tableau, Qlikview, D3js or similar tools is a plus
• 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.
• Experience with IQVIA data sets
• Ability to derive, summarize and communicate insights from analyses
• Organization and time management skills
• Expertise in managing and analyzing a range of large, secondary transactional databases is required.
• Statistical analysis and modelling background
• ML a plus
• Statistical Analysis & Modelling: Design of Experiments, Time Series, Regression, Applied Econometrics and Bayesian methods.
• Data Mining, Predictive Modelling & Machine Learning algorithms.
• Optimization & Simulation.

Desirable Skills/Experience:

• Strong leadership and interpersonal skills with demonstrated ability to work collaboratively with a significant number of business leaders and cross-functional business partners.