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What you’ll bring

All qualifications

Core experience

Experience: * 7–10 years of professional experience in data science or advanced analytics.
Deep understanding of AI/ML principles and frameworks

Preferred experience

Experience in Pharmaceuticals, Life Sciences, or FMCG is highly preferred.

Qualification wording

Experience: * 7–10 years of professional experience in data science or advanced analytics.

Deep understanding of AI/ML principles and frameworks

Experience in Pharmaceuticals, Life Sciences, or FMCG is highly preferred.

Education & alternatives

REQUIREMENTS Education: Master’s or PhD in Science, Engineering, or a related quantitative field. Experience: * 7–10 years of professional experience in data science or advanced analytics.

Tools in this posting

AWS
Azure
Python
Databricks

Source

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 high-performing in production.

Technical Stack: - Expert proficiency in Python - Deep understanding of AI/ML principles and frameworks

Job description

View original posting ↗

SUMMARY OF THE ROLE

As a core member of the Advanced Analytics team, you will bridge the gap between complex data science and pharmaceutical commercial strategy. You will design and deploy advanced analytical solutions—ranging from predictive modeling to Generative AI—to optimize sales force effectiveness, enhance marketing precision, and drive data-led decision-making across AZ China’s commercial portfolio.

ROLE & RESPONSIBILITIES

1. Advanced Analytics & Al Modeling

Design Business Driver Analytics by identifying key commercial performance indicators with leveraging causal inference or any other approaches to uncover true drivers of business impact
Architect and deploy modular analytical frameworks that enable non-coding business users to perform self-service diagnostic deep-dives
Develop intelligent process automation (IPA) driven solutions to streamline major commercial excellence tasks and optimize the business-ready results recommendation

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 high-performing in production.

4. Continuous Innovation

Always 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 Science, Engineering, or a related quantitative field.

Experience: * 7–10 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 AI/ML principles and frameworks
Practical & expertise in utilizing SOTA LLMs and coding agents

Soft Skills:

Strong business acumen and the ability to "tell a story" with data
Project management skills with an agile mindset
Experienced and enthusiastic in prompt engineering

Language: Fluency in English (written and verbal).

Date Posted

04-8月-2026

Closing Date

30-10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.

Your next step

Have your CV and examples of relevant work ready.
Check the listed location, eligibility and core experience before starting.
Ask the employer about the salary range before committing time to the process.

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Source & posting history

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Pay

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Location & working pattern

China

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Work authorization

30-10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.

Open source at astrazeneca.wd3.myworkdayjobs.com ↗Read the full description ↓