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About the Role

A lead Data Scientist (DS) is an expert in Real World Data (RWD) analysis, providing scientific expertise for evidence generation to address key research questions and define target populations. This role ensures research and analyses represent cutting-edge science, methodologies, technologies, processes, and solutions in the pharmaceutical industry. The Lead Data Scientist reports to the Director of Data Science, Medical.

Responsibilities

Lead/co-lead observational/database research and data analysis, including Market/R&D analysis.
Assess study design, target population, data source, data handling, and analytical methods, providing clear epidemiological input.
Oversee vendors, managing timelines, output quality, resources, and costs for assigned research.
Survey and assess necessary database information, recommending suitable databases for research/analytical purposes.
Develop fit-for-purpose AI solutions.
Implement AI (including Generative AI) to simplify and advance Data Science tasks.
Support PARCS initiatives led by the Pharmacovigilance department.

Requirements

Design, analyze, interpret, and publish research in Data Science, Epidemiology, Clinical, or Statistics.
Manage and/or lead teams conducting clinical/epidemiological research, data analysis, and interpretation for efficacy, safety, clinical effectiveness, and epidemiological assessments.
Author manuscripts on specialized topics.
Review, assess, and utilize Real-World Data for research to address clinical/research questions.
Network, integrate, and use EMR/EHR data for clinical/epidemiological research.
Apply bioinformatic methodologies to analyze medical data/databases/scientific research.
Apply appropriate study designs and analytical methods to observational, epidemiological, and pragmatic interventional studies, aligning business and scientific objectives.
Lead the interpretation of scientific data, translate findings into appropriate messaging, and draft manuscripts for scientific publications.
Take a leadership role in analyzing medical evidence gaps, identifying opportunities/requirements for evidence generation, and integrating them into clear evidence plans within cross-functional teams.
Assess the scientific feasibility of using/integrating databases for research purposes.
Develop AI for efficient daily work processes.
Manage projects through planning, execution, and assessment, applying tools, frameworks, and concepts to enhance team effectiveness and performance.
Possess solid communication and interpersonal skills for effective leadership, coaching, and collaboration.
Develop AI prompts for accurate responses.
Apply health technology assessments to clarify drug characteristics.
Read/write scientific documents, including data speculation, in Japanese and English.
Communicate and discuss IT/bioinformatics topics with key stakeholders and experts in Japanese and English.
Make English presentations to lead and facilitate research discussions in global meetings.
Create training plans for applications.
Harmonize processes with global standards.
Communicate with external experts to identify suitable computer environments.
Learn new methodologies and knowledge in machine learning and neural networks.

Skills

Data Science
Real World Data (RWD) analysis
Epidemiology
Clinical research
Statistics
AI development
Generative AI
Bioinformatics
Machine learning
Neural networks
Project management
Communication
Interpersonal skills
Leadership
Coaching
Collaboration

Location

Osaka
Tokyo

Work Type

Full-time

Experience Level

Lead
Expert

Education Level

Master’s degree in public health or equivalent
Master’s degree in Data Science/Engineering/Pharmaceutical science/biostatistics with sufficient experience in clinical development/epidemiological research
PhD in Data Science/Engineering/Pharmaceutical science/biostatistics or MD degree (desirable)

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.