Senior Clinical Data Scientist/Staff/Experimental Medicine Japan D&A (Shinagawa, Japan, Tokyo)
About this opportunity
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
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Job details
How this role compares
Computed from every other active Biostatistics & Data Science role in our database, not just this employer's listings.
We currently track 62 comparable Senior Biostatistics & Data Science roles across 16 biopharma companies.
Salary context
22 of 62 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 62 comparable roles
+ 7 more countries
Seniority mix
62 of 62 peers have a known seniority level
Therapeutic area mix
1 of 62 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.