【AstraZeneca】【Medical】ﾒﾃﾞｨｶﾙ本部 ｴﾋﾞﾃﾞﾝｽ&ｵﾌﾞｻﾞﾍﾞｰｼｮﾅﾙﾘｻｰﾁ統括部, Data Scientist Full-time

Lead Data Scientist

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

Qualification (Experience & Skill etc.)

Experience

•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

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

License

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)

Nice to have

•PhD in Data Science/Engineering/Pharmaceutical science/biostatistics or MD degree is desirable

Skill-set

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

Nice to have

•Develop prompt of AI to get accurate answers

•Apply health technology assessments to make clear drug characteristics

Language

Mandatory

Japanese： Read/write scientific documents including data speculation in Japanese Communicate/discuss IT/bioinformatics topics with the key stakeholders and experts in Japanese practically

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

Others

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

Work Location

Osaka or Tokyo

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.