AstraZenecaCETCutomer Experience & IT, Associate Director Data Scientist

The Associate Director Data Scientist is responsible for applying advanced analytics machine learning epidemiology and real-world data methods to support AstraZeneca Japans commercial PDCA cycle and evidence-based decision-making. The role builds and maintains models for territory planning HCP targeting performance monitoring sales target setting new patient forecasting gap analysis corrective action recommendations and evaluation of commercial interventions. It also leads root cause analysis to explain performance gaps across HCPs facilities regions channels and time periods.
The role leverages Japan-specific real-world data sources such as MDV JMDC NDB and DPC together with public health and policy data to generate insights for market shaping brand strategy patient journey analysis care pathway optimization HTA value demonstration and post-marketing surveillance. Epidemiological methods are used to estimate patient populations diagnosis rates treatment patterns and care gaps across therapy areas.
The position develops forecasting and scenario simulation models that incorporate epidemiology market dynamics competitive activity policy signals and pricing assumptions. These models inform long-range planning brand planning investment decisions and resource allocation.
Technically the role designs analytical pipelines and platforms that integrate structured data RWD and public information for scalable machine learning applications. It promotes modern methods such as deep learning NLP agentic AI and parallel computing while ensuring model quality reproducibility version control monitoring and retraining.
The role also partners with brand teams market access medical affairs business excellence IT external vendors and analytics partners to translate business questions into analytical solutions manage project delivery and communicate insights through clear visualization documentation and storytelling. Finally it contributes to capability building by mentoring junior professionals promoting analytical best practices and supporting the CET data science community.

Experience

Mandatory

7 years of experience in data science machine learning or quantitative analytics with substantive project delivery
5 years of experience in pharmaceutical healthcare or life sciences industry strongly preferred (consulting experience in pharma commercial analytics also valued)
Demonstrated experience building and deploying ML models in a production environment
Demonstrated experience working with real-world data (claims EHR registry data) epidemiological methods and public health data sources
Experience leading cross-functional analytical projects with both business and IT stakeholders
Experience managing project scope schedule and outcome quality across multiple parallel workstreams
Experience managing senior stakeholder expectations to maximise value for both business partners and the analytics team

Skill-set

Mandatory

Strong analytical thinking with ability to translate complex business questions into rigorous analytical frameworks
Solid business acumen with understanding of pharmaceutical commercial dynamics brand lifecycle and market access
Strong communication skills able to explain complex analytical concepts to non-technical stakeholders through clear documentation and visualisation
Proven leadership capability able to mentor junior team members and lead small project teams
Strategic mindset with the ability to prioritise high-impact opportunities and manage detailed tasks across multiple parallel projects
Effective collaborator across business IT and external vendor relationships
Business-level proficiency in Japanese and English

Languages

Mandatory

JapaneseNative

EnglishBusiness

Career LevelE

Work LocationOsaka or Tokyo

Date Posted

Closing Date

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.