Senior Data Scientist (Medical本部 EOR Data Science)

Job Description

Data Scientist(DS) is a key player of evidence generation in Medical division of AZ KK. Therefore, DS surely plays the following roles. DS directly reports to the director of Data Science, EOR.

Responsibilities

1. Advice/co-leading of AZSS
To provide advises about study design, endpoints, analysis, and interpretation of study result from an Epidemiological point of view and lead observational/database research with team members in Medical Div
2. Assessment of study design/target population/data source/data handling
To review plans of observational/database research and support for necessary documentations(clinical study protocol, Statistical analysis plan, speculation, and clinical study report/manuscript)
3. Oversight of venders (timeline management, quality of outputs, & resource)
To oversee vender performances to achieve responsible studies effectively
4. Survey the necessary information for data assets
To survey databases that AZ is/will be able to access for using our research

Qualifications

• Make protocols for clinical trial(CT)/observational study(OS)
• Interpret research results and make presentations at the academic association meetings/manuscripts
• Possible target positions including: Epidemiologist (public health)/HEOR/ Statistician(STAT)/Clinical research Associate(CRA)/Data Management (DM)/Project leader (PM) in clinical development

• Experience in reviewing, assessing and using Real-World data for the research purposes to address clinical / research questions
• Networking, integrating and using electronic medical records (EMR)/electronic health record(EHR) 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, analyzing the health economics/technology and crafting value propositions

License

• Master degree in Engineering, Science (Math/Physics/Public health/informatics) or equivalent
• Professional Data analytics

• PhD of the Public health, Epidemiology & Biostatistics is desirable
• Individuals holding MD/pharmaceutical science degree

Skill Set

• Programming skill for Python/R/SAS/other language
• Ability in defining data specification of health care data for research purposes
• Medical writing/Publication of own researches
• Ability in discussing study plan/result interpretation with external experts
• Scientific communication skill

On top of the mandatory skill-set above,

• Design, construct and implement the process/platform of database research by using data
• Identification/Assessment of healthcare data for pharmacoepi studies

Language

• Japanese：

- Read/write scientific documents including data speculation in Japanese

- Communicate, and discuss data analytic topics with the key stakeholders and experts in Japanese practically

• English

- Read/write scientific documents including data speculation in English

- Communicate, and discuss data analytic topics with the key stakeholders and experts in English practically

- Make an English presentation leading and facilitating research discussions in the global meetings

Others

• Make training plan about applications
• Harmonize process with global
• 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

Career Level

• D or E

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.