Job Title: Advanced Analytics Manager

Location: London

Competitive salary and benefits

Introduction to role:

Are you ready to turn complex commercial and medical questions into robust evidence that changes decisions and improves outcomes for patients? Do you thrive on owning the end-to-end journey from problem framing through to communicating actionable insights to senior leaders?

Reporting to the Head of Insights & Analytics, you will play a pivotal role in AstraZeneca UK’s analytics transformation. As an individual contributor and analytical thought partner, you will lead the technical design, development, validation and industrialisation of advanced analytics, statistics and data science solutions that answer critical business questions. Your work will set the standards by which models are trusted and used in business-critical decision making.

This role is hands-on, strategic and influential. You will work across the product lifecycle and partner closely with Sales, Marketing, Medical, Market Access, Commercial Operations, Data and Technology colleagues to translate ambiguity into rigorous evidence and practical recommendations. Alongside immediate delivery, you will shape the future of analytics by advancing machine learning, AI-enabled analytics and next-generation capabilities such as Commercial Digital Twin.

Accountabilities:

High-impact advanced analytics delivery: Design and deliver advanced analytics projects addressing critical business questions; translate ambiguous challenges into robust analytical approaches and actionable recommendations; lead end-to-end delivery from problem framing and methodology selection through execution and communication; personally develop complex Python solutions including data preparation, feature engineering with data engineers, model estimation, validation, sensitivity analysis and reproducible documentation; combine internal and external data sources to generate new insights and communicate sophisticated outputs simply and compellingly; apply relevant approaches including promotional mix modelling, patient and customer analytics, promotional effectiveness and Digital Twin to influence strategic and operational decisions.

Analytical innovation and next-generation capability: Identify opportunities to apply emerging analytical techniques, machine learning and AI to commercial and medical challenges; explore novel data sources, methodologies and technologies that create competitive advantage or improve patient outcomes; develop a deep understanding of the UK business through partnership and collaboration; help shape next-generation advanced analytics capabilities, including Commercial Digital Twin and AI-enabled analytics, translating innovation into practical applications that scale.

Statistical standards, causal inference and model assurance: Serve as the UK authority for data science and set technical and statistical standards for methodology, causal inference, model validation, interpretation and communication of uncertainty; independently review and challenge models developed internally or by external partners; ensure assumptions, limitations, potential bias and strength of evidence are transparent before outputs inform decisions; determine appropriate methodology for the highest-risk analyses; lead application and assurance of causal inference, experimentation and uncertainty-quantification methods to strengthen confidence in evidence-based decisions.

Analytical leadership and strategic partnership: Act as a subject matter expert in statistics, modelling and analytical methodology; challenge analytical approaches to improve quality and reliability; promote best practice in statistical thinking across the organisation; build strong relationships across key UK functions and act as a strategic thought partner; collaborate closely with Sales, Marketing, Market Access and IBEX colleagues, particularly Data, Technology, Commercial Operations and Insights, to ensure analytics is a trusted source of expertise, innovation and strategic challenge.

Essential Skills/Experience:

- Relevant advanced analytics, data science, statistics, econometrics or equivalent technical expertise demonstrated through experience

- Deep experience in advanced analytics, data science, statistics, econometrics or a related discipline

- Experience applying advanced analytical techniques to commercial business problems within life sciences, healthcare, consulting or a comparable industry

- Proven track record leading end-to-end analytical projects from problem definition through to business impact

- Experience working with large, complex and diverse datasets

- Experience applying methodologies such as marketing mix modelling and impact modelling and leveraging AI and machine learning

- Deep knowledge of statistics, analytical methods, underlying mathematics, assumptions, trade-offs, interpretability and limitations

- Demonstrated ability to influence decision-making through analytics and evidence

- Ability to communicate complex analytical findings clearly to senior stakeholders

- Proficiency in tools such as Python, R, SQL, Power BI, Databricks or equivalent advanced analytics platforms

Desirable Skills/Experience:

- Relevant degree or advanced technical qualification in data science, statistics, econometrics, mathematics, computer science or a related discipline

- Experience with Git and cloud technologies for deployment, including platforms such as Snowflake or Databricks

- Experience with causal inference, experimentation and uncertainty quantification

Why AstraZeneca:

Join a team where analytics and technology directly advance our ability to deliver life-changing medicines. You will be part of a company on a decisive journey to become data-led, with the investment and platforms to scale modern analytics, AI and machine learning across the enterprise. Expect to work at pace with cross-functional partners, often bringing unexpected teams into the same room to unleash bold thinking, and to use modern tools to put trustworthy data into every decision. We value curiosity and ambition alongside kindness, encourage experimentation in a modern technology environment, and recognise the big contributions that move science into the hands of patients faster.

Date Posted

Closing Date