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About the Role

The Associate Director, Data Scientist applies advanced analytics, machine learning, and epidemiological methods to support AstraZeneca Japan’s commercial operations and decision-making. This role involves building and maintaining models for various commercial functions, leading root cause analysis for performance gaps, and leveraging Japan-specific real-world data to generate strategic insights. The position also develops forecasting and scenario simulation models, designs analytical pipelines for scalable machine learning applications, and collaborates with cross-functional teams to deliver analytical solutions. Additionally, the role contributes to capability building through mentoring and promoting best practices within the data science community.

Responsibilities

Apply advanced analytics, machine learning, and epidemiology methods to support commercial operations.
Build and maintain models for territory planning, HCP targeting, performance monitoring, sales target setting, new patient forecasting, gap analysis, corrective action recommendations, and evaluation of commercial interventions.
Lead root cause analysis to explain performance gaps across HCPs, facilities, regions, channels, and time periods.
Leverage Japan-specific real-world data sources (MDV, JMDC, NDB, DPC) and public health/policy data to generate insights for market shaping, brand strategy, patient journey analysis, care pathway optimization, HTA, value demonstration, and post-marketing surveillance.
Use epidemiological methods to estimate patient populations, diagnosis rates, treatment patterns, and care gaps.
Develop forecasting and scenario simulation models incorporating epidemiology, market dynamics, competitive activity, policy signals, and pricing assumptions.
Inform long-range planning, brand planning, investment decisions, and resource allocation with model outputs.
Design analytical pipelines and platforms integrating structured data, RWD, and public information for scalable machine learning applications.
Promote modern methods such as deep learning, NLP, agentic AI, and parallel computing.
Ensure model quality, reproducibility, version control, monitoring, and retraining.
Partner with brand teams, market access, medical affairs, business excellence, IT, external vendors, and analytics partners.
Translate business questions into analytical solutions.
Manage project delivery and communicate insights through clear visualization, documentation, and storytelling.
Contribute to capability building by mentoring junior professionals.
Promote analytical best practices and support the CET data science community.

Requirements

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.

Skills

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.

Location

Osaka or Tokyo

Work Type

Full-time

Experience Level

Associate Director

About the Company

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.

Equal Opportunity

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.