Jobs at AstraZeneca Pharma Limited

The Senior Analyst – Brand Analytics will drive data-driven commercial decision-making by analyzing healthcare data and generating actionable insights to improve brand performance, optimize marketing investments, and enhance patient outcomes. The role requires 6–8 years of experience in pharmaceutical, biotech, or healthcare analytics, with strong expertise in Python, R, SQL, statistical modeling, and secondary healthcare datasets, including claims, EMR/EHR, and patient-level data. 

• Commercial Analytics and Insight Generation: Partner with assigned brand teams to shape strategy and execution through meticulous, data-driven analysis that informs where to focus and why it matters.
• Opportunity Identification: Size markets, uncover HCP and patient opportunities, and assess whitespace to prioritize investments that drive measurable impact.
• Customer Segmentation and Targeting: Build and operationalize segments that sharpen targeting across channels and optimize field and non-personal engagement.
• Marketing Mix and return on investment: Quantify channel effectiveness, run attribution and econometric analyses, and guide budget reallocation to enhance returns.
• Test-and-Learn Experimentation: Design and evaluate smart business experiments and pilots; establish success metrics and embed lessons into ongoing plans.
• Market Simulation and Patient Flow Modelling: Create simulations and patient journey models to pressure-test scenarios and inform trade-off decisions.
• Advanced Analytics and Data Science: Develop robust, production-ready analytics in Python and SQL (and PySpark where relevant), applying statistical methods, predictive modelling, time series, regression, econometrics, and Bayesian techniques.
• Secondary Healthcare Data Mastery: Work extensively with large, longitudinal datasets (claims, EMR/EHR, prescription and patient-level data, including IQVIA) to generate trusted insights.
• Data, Platforms and Automation: Use Databricks and modern data environments to build scalable, reusable assets; champion standard processes in coding, version control, documentation, and reproducibility.
• Analytics Automation: Find opportunities to automate recurring analytics, apply AI-assisted coding, and standardize frameworks to boost speed and quality.
• Collaborator and Cross-Functional Collaboration: Collaborate with Marketing, Medical, Market Access, Sales, Forecasting, and US Sales Force Operations; manage several priorities without compromising quality or turnaround time.
• Executive Communication and Storytelling: Synthesize sophisticated outputs into clear, decision-ready insights for senior leaders via decks, dashboards, and executive updates; frame recommendations in business terms.
• Continuous Improvement: Contribute to a culture of innovation and analytical excellence, sharing knowledge and elevating standards across the team.

Education:

• Bachelor’s degree or equivalent experience in a quantitative field such as Engineering, Statistics, Economics, Applied Mathematics, Computer Science, Data Science, Operations Research or related field
• Advanced degree or equivalent experience (Master’s / MBA / PhD) preferred

Experience:

• 6–8 years of experience in Pharmaceutical / Biotech / Healthcare analytics
• Strong experience working with secondary healthcare data (claims, EMR/EHR, patient-level datasets)
• Demonstrated experience delivering commercial analytics with measurable business impact

Technical skills:

• Strong hands-on experience with Python, R, SQL (PySpark preferred)
• Databricks or similar analytics platforms
• Data visualization experience with tools such as Power BI, Tableau, MicroStrategy, QlikView (or similar)
• Advanced Excel and PowerPoint skills for executive communication
• Expertise in statistical analysis, modelling, and data mining
• Experience with IQVIA or similar syndicated data sources

Core proficiencies:

• Strong analytical problem-solving capability
• Ability to translate data into actionable commercial insights
• Excellent communication and customer management skills
• Ability to handle multiple projects in a fast-paced environment

Desirable skills/experience

• Experience in Oncology analytics or strong understanding of patient pathways and treatment landscapes
• Exposure to machine learning, optimization, and simulation techniques
• Experience with Big Data / Spark-based environments
• Consistent track record to lead analytics initiatives and influence senior commercial partners
• Strong critical thinking with the ability to connect analytics to brand and business strategy