Senior Manager-Advanced Analytics
China
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingBuild predictive models and causal analyses to find true drivers of commercial performance
Create modular analytics frameworks so non-coding users can run self-service deep-dives
Develop intelligent process automation to streamline commercial excellence tasks
Deploy models in cloud environments following MLOps practices to keep them performing in production
From the employer’s posting
Business Driver Analytics by identifying key commercial performance indicators with leveraging causal inference
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
Ensure the scalability and robustness of models by following MLOps best practices, ensuring models remain high-performing in production.
What you’ll bring
All qualificationsCore 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
- Python
- AWS
- Azure
- Databricks
Source — Tool mentions in context
Technical Stack: - Expert proficiency in Python - Deep understanding of AI/ML principles and frameworks
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.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 5, 2026 · 86 days ago
- Recorded sightings
- 201
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
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-2026Closing Date
30-10月-2026AstraZeneca 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.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
China
Working pattern and location restrictions need checking in the full posting.
- 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.
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