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【AstraZeneca】【Medical】メディカル本部 エビデンス&オブザベーショナルリサーチ統括部, Lead Statistician

AstraZeneca

2 Locations permanent

Posted: February 6, 2026

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Quick Summary

A lead statistician is responsible for conducting Real World Data analysis, including statistical design, analysis, and sample size calculation in collaboration with Data Scientist.

Job Description

■ 職務内容 / Job Description

A lead statistician (STAT) is a key player of conducting Real World Data (RWD) analysis of AZ KK so that those scientific values are enhanced. Therefore, STAT surely has the following responsibilities: 

・Lead AZSS and Post marketing database (DB) research from a statistical point of view including research design, statistical analysis, and sample size calculation in collaboration with Data Scientist (DS).
・Assess study outcomes/study design/results, interpret research results and make descriptions with statistical insights (all Real World Data analyses including Market/R&D requests)
・Implement innovative methodology such as prediction or causality
・Use AI for automating regular tasks
・Look for statistical topics related to observational/database research, do researches, and make manuscripts  

STAT directly reports to the Director of Data Science.

■ 応募資格(経験、資格等) / Qualification (Experience & Skill etc.)

【経験 / Experience】

<必須 / Mandatory>

・Plan study design, sample size calculation, analysis in clinical trials or DB researches
・Statistician/Statistical programming in clinical development or DB researches
・Research for statistical methodology

・Make a publication (presentation at Academic association meetings/manuscripts)

<歓迎 / Nice to have>

・Experience in reviewing, assessing and using Real-World data for the research purposes to address clinical / research questions
・Networking, integrating and using EMR(electronic medical records)/EHR(electronic health record) data for the clinical / epidemiological research
・Using / applying bioinformatics methodologies to analyze medical big data / database / scientific research outcomes
・Health Technology Assessment in building models, estimating Health Care resources, analysing the health economics/technology and crafting value propositions

【資格 / License】

<必須 / Mandatory>

・Master degree in Statistics, Engineering, Science (Math, Physics, Iinformatics) or equivalent (MD/Public health/pharmaceutical science degree may be acceptable)
・Professional of statistics

<歓迎 / Nice to have>

・PhD in Biostatistics

【能力 / Skill-set】

<必須 / Mandatory>

・Programming skill of R, & SAS in clinical study/DB research
・Implementation of new technology & methodology 
・Publication/Medical writing of own research
・Exchange of insights about statistical subjects with external
・Presentation at meetings about study design, results, and statistical methodology

<歓迎 / Nice to have>

・ Programming skill of Python
・Lead meeting of which agenda includes statistical topics

【語学 / Language】

<必須 / Mandatory>

・Read/write statistical documents including study population in English/Japanese
・Communicate, and discuss Statistics/bioinformatics topics with the key stakeholders and experts in English/Japanese practically
・Make a English presentation, organize and facilitate the research/clinical study in the global meetings

【その他 / Others】

<必須 / Mandatory>

Skill/knowledge
・Interpretation of analysis results and present external members at the Academic conference/decision making meetings
・Innovative methodology for analysis (e.g. Machine learning & Neural network) 

【キャリアレベル / Career Level】

E

【勤務地 / Work Location】

Osaka or Tokyo

Date Posted

06-2月-2026

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.

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