ROLE & RESPONSIBILITIES

1. Advanced Analytics & Al Modeling

• Develop and implement end-to-end machine learning models to solve commercial challenges, including Marketing Mix Modeling (MMM) and Next Best Action (NBA).
• Develop high-accuracy sales forecasting models. Integrate external macro-factors and internal promotional data to enhance strategic planning and risk management.
• Explore and integrate of GenAI/LLM applications to enhance internal productivity & analytics tools
• Develop intelligent process automation (IPA) to accelerate and optimize tasks such as sales deployment, target setting, resource allocation and etc.

2. Strategic Business Partnership

• Collaborate closely with commercial stakeholders to translate "business questions" into "data science problems."
• Act as a subject-matter expert, presenting complex technical findings to non-technical leadership in a clear, "story-driven" manner.

3. Data Engineering & MLOps

• Partner with IT and global technology teams to implement solutions within cloud environments (e.g., AWS, Azure, Databricks).
• Ensure the scalability and robustness of models by following MLOps best practices, ensuring models remain accurate and high-performing in production.

4. Continuous Innovation

• Stay at the forefront of AI/ML trends.
• Proactively identify new data sources or analytical methodologies that can provide a competitive edge for AZ.

REQUIREMENTS

Education: Master’s or PhD in Data Science, Computer Science, Statistics, or a related quantitative field.

Experience: at least 5–8 years of professional experience in data science or advanced analytics.

• Proven track record of delivering end-to-end ML products (from data cleaning to production).
• Experience in Pharmaceuticals, Life Sciences, or FMCG is highly preferred.

Technical Stack:

• Expert proficiency in Python
• Deep understanding of ML frameworks
• Hands-on experience with GenAI/LLM application development (Prompt engineering, RAG, etc.).
• Familiarity with Cloud platforms (AWS/Azure) and SQL.

Soft Skills:

• Strong business acumen and the ability to "tell a story" with data.
• Project management skills with an agile mindset.

Language: Fluency in English (written and verbal).

Date Posted

05-1月-2026

Closing Date

27-2月-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.