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AstraZeneca

Senior Analyst - Commercial Pharma Analytics

AstraZeneca is hiring a Senior Analyst - Commercial Pharma Analytics in Chennai, India. Level rates it ; you can apply on AstraZeneca.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • Tools and skills the posting cites include Databricks, SQL and Python.
  • Level classifies it as a senior role.
  • Level lists 1,200+ other open roles at AstraZeneca.
  • The role was posted within the past two weeks.

AI in this role

Senior analyst managing data quality and predictive commercial analytics for pharma brand strategies.

databrickssqlpython
data-qualitypredictive-modelinganalyticsdata-governance

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.

Strong communication and influencing skills with demonstrated ability to develop and effectively present succinct, compelling reviews of independently developed analyses infused with insight and business implications/actions to be considered.

Strategic and critical thinking with the ability to engage, build and maintain credibility with Commercial Leadership Team.

Strong organizational skills and time management; ability to manage diverse range of simultaneous projects.

Knowledge of AZ brand and Science (Oncology in particular).

Experience using Big Data, is a plus. Exposure to SPARK is desirable

Should have Excellent Analytical, Problem Solving ability. Should be able to grasp new concepts quickly

When we put unexpected teams in the same room, we ignite bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Here you will join a high-performing, digitally savvy community that blends scientific purpose with practical impact, placing ethics and transparency at the heart of everything we do. You will work shoulder to shoulder with colleagues across the enterprise, harnessing modern platforms and data to drive meaningful change for patients and the business. We bring together diverse problem solvers to ignite bold ideas, support each other with kindness and ambition, and give you the autonomy to turn insight into action while growing your craft on projects that truly matter.

Call to Action:

Step into this role to elevate the quality of data that powers critical brand decisions and accelerate your impact on patients’ lives—submit your application and shape what science can achieve next.

Date Posted

22-Oct-2026

Closing Date

25-Oct-2026

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

How we rate this

Senior Analyst - Commercial Pharma Analytics at AstraZeneca rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data QualityPredictive ModelingAnalyticsData GovernanceDatabricksSQLPython

Questions you could be asked

  1. Tell me about a project where data quality was part of your work. What did you do?
  2. Tell me about a project where predictive modeling was part of your work. What did you do?
  3. Tell me about a project where analytics was part of your work. What did you do?
  4. Tell me about a project where data governance was part of your work. What did you do?
  5. Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Data Quality, Predictive Modeling, Analytics, Data Governance, and Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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