Associate - Data Analyst

Associate - Data Analyst Job Title: Associate - Data Analyst Career Level: C2 Introduction to role:

Are you ready to turn complex data into clear decisions that advance our medicines and accelerate business outcomes? Join a distributed team that powers transformation through predictive analytics, smart automation, and rigorous data modeling. Your work will directly enable faster, smarter choices that drive impact for patients and the enterprise.

You’ll partner with internal customers to understand their data and analytical needs, champion local insight in strategic decisions, and deliver high-quality reporting at pace. You will test, learn, and scale new capabilities—building consistency and efficiency through automated processes—while pushing the boundaries of what data can do. Do you thrive in fast-moving environments where you can connect the dots, challenge how things have always been done, and see your analysis turn into action?

Accountabilities:

• Customer Insight Leadership: Translate local customer insights into clear guidance for strategy and resource allocation, ensuring analysis drives decisions.

• BAU Analytics Delivery: Own the preparation and delivery of recurring analytics reports, meeting stakeholder needs with reliability and precision.

• SLA and Turnaround: Maintain tight turnaround times and quality against agreed SLAs, continuously refining workflows to improve speed and consistency.

• Quantitative Methods Evaluation: Explore, test, and adopt new quantitative approaches and technologies that raise analytical standards and outcomes.

• Capability Deployment: Support the development and rollout of analytics capabilities across teams, enabling scalable, reusable solutions.

• Continuous Improvement: Instill a culture of experimentation, measurement, and iteration to elevate analytical practices and business performance.

• Cross-functional Integration: Understand how analytical work connects across functions, aligning outputs to shared goals and enterprise priorities.

• External Scanning: Monitor leading analytic advancements inside and outside pharma, assessing relevance and value for the organization.

• Data Access and Quality: Source, validate, and integrate data from multiple tools and platforms to build robust, decision-ready datasets.

• Communication and Storytelling: Summarize findings with clarity through written reports, dashboards, and presentations tailored to diverse audiences.

• Business Impact: Move beyond reporting to recommend actions, quantify value, and track results that create a competitive advantage.

Essential Skills/Experience:

• The candidate will also be required to continuously evaluate new quantitative analysis methods and technologies.

• Develop a deep understanding of internal customers' data and analytical needs focusing on the customer-facing model leadership.

• Champion the use of local customer insight in strategic and resourcing decisions across the business.

• Support, maintain and deliver Analytics Reports in BAU to the respective collaborators.

• Maintain tight Turn Around Times and at most quality as per agreed SLA.

• Can support the development and deployment of such capabilities across the organization.

• Instills a culture of continuous improvement, testing, and deployment of new capabilities for the business.

• Develop innovative analytical practices to create and sustain competitive advantage.

• Access appropriate information via a variety of tools and sources

• Summarize and present findings through various communication channels.

• Capability in applying deeper technical skills and knowledge that is shared across the functional area (e.g., deep knowledge of key data sets, modeling capabilities, etc.)

• Demonstrate a high level of understanding of the points of integration of our work and that of our colleagues.

• Monitors the external environment to stay up to date on leading analytic capabilities, both within and outside of pharma, which can be applied within the organization.

Desirable Skills/Experience:

• Proficiency with SQL, Python or R, and experience building reproducible analytics pipelines

• Hands-on experience with BI and visualization tools (e.g., Power BI, Tableau) and dashboard design principles

• Familiarity with statistical modeling, experimentation design, and basic machine learning techniques

• Experience working with cloud data platforms (e.g., Azure) and modern data engineering practices

• Knowledge of pharma or healthcare datasets and the ability to translate analysis into commercial or operational value

• Strong stakeholder engagement skills, including requirements gathering and prioritization in fast-paced environments

• Ability to quantify impact, define success metrics, and track outcomes for continuous improvement

When we put unexpected teams in the same room, we unleash 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, your curiosity and craft meet a clear purpose: harness data to shape decisions that help patients. We bring unexpected teams together to spark bold thinking, backed by investment in modern tools and a culture that values kindness alongside ambition. You’ll join a connected, globally minded community where sharing, coaching, and rapid execution are the norm—so you can test new ideas, learn from diverse perspectives, and build solutions that move the whole enterprise forward.

Step into this role to shape a tech-enabled enterprise and create insight that changes outcomes—your next challenge starts here!

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.