【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, Data Scientist
AstraZeneca is hiring a 【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, Data Scientist in Tokyo, Japan. Level rates it ; you can apply on AstraZeneca.
Level's read on this job
- Level rates this data scientist role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Generative AI, AI Tools and data science among its tools and skills.
- Level classes it as a lead role.
- AstraZeneca has 1,200+ other open roles on Level.
AI in this role
Lead real-world data analysis and observational research while integrating AI solutions into medical data processes.
■ 職務内容 / Job Description
A lead Data Scientist (DS) is an expert role in Real World Data(RWD) analysis to provide scientific expertise in evidence generation so that key research questions are sufficiently addressed and set target population for research. And all researches/analyses are planned and delivered in a way that represent cutting-edge science, methodologies, technologies, processes, and solutions in the Pharm industry. Lead Data Scientist reports to director of Data Science, Medical.
•Lead/co-lead observational/database research and data analysis including Market/R&D analysis
•Assess study design/target population/data source/data handling/analytical method and give clear inputs from an epidemiological point of view
•Oversee venders and manage timeline, quality of outputs, resource, & cost of their responsible researches
•Survey & assess the necessary information for database and recommend database that fits for research/analytical purpose
•Develop AI use fit for purpose
•Implement AI (including Generative AI) to their work process not only for simplifying DS regular tasks but also for advancing them
•Support for PARCS led by Pharmacovigilance department
■ 応募資格(経験、資格等) / Qualification (Experience & Skill etc.)
【経験 / Experience】
<必須 / Mandatory>
•Design, analyze, interpret and publish researches for Data Science/Epidemiology/Clinical/Statistics
•Manage, and/or lead group of members who are responsible for conducting clinical/epidemiologic research, analysis of data, reading of the data for efficacy, safety, clinical effectiveness and epidemiological assessments (acceptable even if the leadership is primarily focused on the scientific features)*
*Mandatory only for those with pharmaceutical industry experience
•Make manuscript for their own specialized topics
<歓迎 / Nice to have>
•Reviewing, assessing and using Real-World Data for research purposes to address clinical/research questions
•Networking, integrating and using EMR(electronic medical records)/EHR(electronic health record) data for clinical /epidemiological research
•Using/applying bioinformatic methodologies to analyze medical data/database/scientific research
【資格 / License】
<必須 / Mandatory>
•Master’s degree in public health or equivalent (individuals holding Data Science/Engineering/Pharmaceutical science/biostatistics degree are acceptable, but should have had the sufficient experience specialized in clinical development/epidemiological research)
<歓迎 / Nice to have>
•PhD in Data Science/Engineering/Pharmaceutical science/biostatistics or MD degree is desirable
【能力 / Skill-set】
<必須 / Mandatory>
•Apply appropriate study design & analytical methods to observational / Epidemiological / pragmatic interventional studies to combine business and scientific agenda
•Lead the interpretation of the scientific data, the translation to the appropriate messaging and drafting manuscript of relevant scientific publications
•Take a leadership in analyzing medical evidence gap, spotting opportunities/requirements for evidence generation and integrate them into a clear evidence plan/option in the cross-functional team
•Assess scientific feasibility in using/integrating databases for the research purposes
•Develop AI for making efficient way for daily work
•Manage project in planning, execution, and assessment, and apply the tools/frameworks/concepts to drive the effectiveness/performance of project teams
•Solid communication and interpersonal skills to enable effective leadership, coaching and collaborations
•Programming skills in at least one of the following languages: SAS, R, or Python
<歓迎 / Nice to have>
•Develop prompt of AI to get accurate answers
•Apply health technology assessments to make clear drug characteristics
【語学 / Language】
<必須 / Mandatory>
日本語 Japanese:
• Read/write scientific documents including data speculation in Japanese
• Communicate/discuss IT/bioinformatics topics with the key stakeholders and experts in Japanese practically
英語 English:
Read/write scientific documents including data speculation in English
• Communicate, and discuss IT/bioinformatics topics with the key stakeholders and experts in English practically
• Make a English presentation leading and facilitating research discussions in the global meetings
【その他 / Others】
<必須 / Mandatory>
• Communicate with external experts to search for suitable computer environment in AZ KK
• Learn new methodology and knowledge with respect to machine learning and neural network
【勤務地 / Work Location】
Osaka or Tokyo
Date Posted
07-8月-2026Closing 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.
How we rate this
【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, Data Scientist at AstraZeneca rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical data scientist job
- $168k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where real world data was part of your work. What did you do?
- Tell me about a project where epidemiology was part of your work. What did you do?
- Tell me about a project where statistical analysis was part of your work. What did you do?
- Tell me about a project where clinical research was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Science, Real World Data, Epidemiology, Statistical Analysis, and Clinical Research. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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