Senior Clinical Data Scientist/Staff/Experimental Medicine Japan D&A

Basic Purpose of the Job Supports the complete clinical/pharmaceutical drug lifecycle process (research, development, market access, and market supply) by providing: Strategic planning and execution Data transformation Descriptive analytics Diagnostic analytics Predictive analytics Prescriptive analytics Work involves data from: Clinical trials Clinical registries Real-world databases Responsibilities include providing: Analytics tools Data outputs Scientific inference and insights May also: Act as an ExpMED Product Owner at the project/asset level Represent ExpMED regarding data science-related activities on projects and assets Key Accountabilities 1. Data Transformation, Analysis & Reporting Responsible for: Transforming, analyzing and reporting data from Phase I-IV clinical trials Supporting complex clinical studies and projects Analyzing data from registries and real-world databases Delivering analytics aligned with project and asset needs Success Measures Quality deliverables Timeline adherence Feedback from development teams, Product Owners (POs), and capability managers 2.

Innovation in Data Science Stay current with developments in data science Explore new transformation and analytical approaches Introduce innovative tools and processes inside and outside BI Success Measures Quality of new analytical solutions Innovation impact Stakeholder feedback 3. Data Storytelling & Communication Present compelling, validated data science stories Explain data science concepts to stakeholders with limited technical backgrounds Communicate insights clearly across BI Success Measures Quality and frequency of presentations Audience understanding and feedback 4.

Specifications & Compliance Ensure data transformation and analysis specifications are: Complete Correct SOP-compliant GxP-compliant Success Measures Quality and regulatory acceptance of specifications 5. Internal & External Support Support colleagues Support internal customers Support external providers on data science activities Success Measures Stakeholder satisfaction Knowledge sharing within the CDS Community of Practice 6.

Cross-Functional Leadership Participate in One Human Pharma working groups Lead ExpMED working groups when applicable Drive data science-related initiatives Success Measures Quality of participation Leadership effectiveness Impact of working group outcomes Feedback from Global Product Owners and Product Owners 7. Product Owner Responsibilities (If Applicable) Support clinical drug lifecycle activities as an ExpMED Product Owner Success Measures Product deliverable quality Leadership effectiveness Timeline adherence Stakeholder feedback 8.

Cross-Functional Collaboration Foster team-based working within ExpMED Collaborate with neighboring functions across BI Perform cross-functional activities when required Success Measures Quality and frequency of collaboration Stakeholder feedback Regulatory & Organizational Requirements Must understand and implement: International Regulations Good Clinical Practice (GCP) Good Statistical Practice ICH regulations across all regions Clinical Development Guidelines Clinical development methodologies Statistical methodologies Therapeutic Area-specific development requirements Internal Requirements BI processes Standard Operating Procedures (SOPs) Clinical Development Plan requirements Additional Regulations (when applicable) Good Laboratory Practice (GLP) Good Manufacturing Practice (GMP) Job Complexity Solves complex but defined problems Mainly operational with limited strategic impact Must consider requirements across multiple functions and departments Interfaces Works closely with teams across BI, including: GCO GPV Therapeutic Areas TMCP GRA Research Development Pharma Supply Represents BI regarding: Statistical planning Data transformation Data analysis Regulatory requests related to trials, projects and assets Job Expertise Required expertise includes: Data Science Understanding and application of key data science principles Advanced capability in: Planning analyses Data transformation Statistical analysis Interpretation of results Reporting Technical Advanced experience with software programming languages relevant to business needs Industry & Clinical Development Advanced understanding of the clinical drug development lifecycle Clinical trial development experience Leadership Project leadership experience required Experience Requirements Master's Degree (MSc): Minimum 3 years experience in: Pharmaceutical industry CROs Regulatory authorities Academic institutions Bachelor's Degree: Minimum 5 years of data science experience Relevant deep expertise may partially compensate for years of experience. Job Impact Responsible for: Analysis of clinical drug lifecycle data at BI Communication of results to internal and external customers Independent decision-making related to analytical activities Delivering insights adapted to customer needs Education Requirements Bachelor of Science (BSc) or Master of Science (MSc) in: Statistics Mathematics Computer Science Data Science Psychology Finance Related quantitative disciplines Required Capabilities Statistical & Scientific Knowledge Strong statistical methodology knowledge Experimental design knowledge Clinical trial design knowledge Understanding of clinical trial terminology Knowledge of information processing in clinical development Advanced Analytics Understanding of advanced statistical concepts used in Data Science Technical Skills Proficient use of relevant programming/software languages Communication Fluent English (Read / Write / Speak) Strong communication and presentation skills Leadership Ability to lead and facilitate meetings Project leadership capability Collaboration Strong teamwork Experience working globally and remotely Effective stakeholder management Interpersonal Skills Ability to interact with: CROs External experts Management Internal stakeholders Problem Solving Proactively identify issues Propose solutions Work independently on routine data science challenges Cultural Awareness Awareness of local, global, internal and external cultures to ensure effective communication and collaboration Quick Candidate Snapshot Ideal profile: MSc + 3 years (or BSc + 5 years) in Data Science, Biostatistics, Clinical Analytics, or a related field Strong statistical analysis and programming skills Experience analyzing clinical trial, registry, or real-world data Understanding of clinical development and pharmaceutical R&D Experience with stakeholder communication and data storytelling Project leadership experience Fluent English Able to translate complex data into business and scientific insights