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Takeda Pharmaceutical

# Senior Manager, Clinical Data Scientist

Bhartiya City, Bengaluru, Karnātaka, India Full-time Manager or lead {'@type': 'MonetaryAmount', 'currency': 'USD', 'value': {'@type': 'QuantitativeValue', 'unitText': ''}} Data & Analytics 

Listed on Takeda Pharmaceutical’s official careers site. Posted October 30, 2026. Check that it is still open and apply there.
[Apply on Takeda Pharmaceutical’s careers site →](https://jobs.takeda.com/job/bengaluru/senior-manager-clinical-data-scientist/1113/102636742544)

[OpenNash Jobs](https://jobs.opennash.com/) / [Takeda Pharmaceutical](https://jobs.opennash.com/companies/takeda-pharmaceutical/) / Senior Manager, Clinical Data Scientist

## Job description

By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.

### Job Description

Objective / Purpose:
- Serve as a Senior Manager-level Clinical Data Scientist within Data & Quantitative Sciences, applying statistical, data science, and analytical methods to support clinical development programs.
- Partner with cross-functional study teams to deliver analysis-ready data, perform quantitative analyses, interpret results, and generate decision-support insights.
- Deliver fit-for-purpose statistical, data science, and advanced analytics activities for assigned studies and study-level workstreams.
- Collaborate with Clinical, Clinical Pharmacology, PSPV, Clinical Data Management, Translational Sciences, Regulatory, Clinical Operations, Statistical Programming, and external partners to support high-quality, traceable, analysis-ready, and submission-ready data.
- Apply modern clinical data science practices, including automation, reusable analytics workflows, and AI/ML-enabled approaches, while maintaining scientific rigor, regulatory awareness, and patient-focused decision making.

### Accountabilities
- Execute clinical data science activities for assigned studies, ensuring timely delivery of high-quality analyses, data review, and quantitative insights that support study objectives.
- Perform exploratory analyses, data visualization, and quantitative assessments using clinical trial, biomarker, external, and real-world data sources.
- Collaborate with Clinical Data Management, Clinical Pharmacology, PSPV, Clinical Operations, and Translational Sciences to support study objectives and evidence generation.
- Translate scientific and clinical questions into analysis-ready datasets, specifications, and reproducible analytical workflows.
- Support integrated data review activities by identifying data trends, inconsistencies, and potential risks requiring further investigation.
- Apply established statistical, machine learning, simulation, and visualization methods to support interpretation of study results and development decisions.
- Contribute to the review of analysis outputs, visualizations, and technical documentation to ensure quality, traceability, and reproducibility of deliverables.
- Review and contribute to analysis outputs produced by internal teams and external partners, ensuring quality and adherence to established standards and processes.
- Identify and communicate risks related to data quality, analytical assumptions, timelines, and quantitative outputs to functional stakeholders.
- Contribute to continuous improvement efforts through automation, reusable code, standard methodologies, and adoption of approved technologies and workflows.
- Contribute to departmental standards, process improvements, and technology adoption initiatives as assigned.
- Share technical expertise and support onboarding and development of less experienced team member Education & Competencies (Technical and Behavioral): Education / Experience
- PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or related field with 5+ years of relevant experience; or MS with 7+ years of relevant experience.
- Experience supporting quantitative analyses and data science activities within pharmaceutical, biotechnology, healthcare research, or other regulated clinical development environments.
- Demonstrated ability to contribute to clinical development decisions through quantitative analysis, data interpretation, and effective communication of evidence.
- Experience working effectively on cross-functional study teams and collaborating across functional disciplines to achieve study objectives.
- Experience working with clinical trial data and one or more additional data types such as biomarker, real-world, external, imaging, digital health, or other high-dimensional data sources. Highest-priority

### Technical Skills
- Strong knowledge of clinical trial design, drug development, endpoints, estimands, biomarkers, data interpretation, and the role of analytics in clinical decision making.
- Strong foundation in statistics and quantitative methods, including longitudinal analysis, survival methods, causal reasoning, simulation, predictive modeling, and communication of uncertainty.
- Hands-on proficiency in R and/or Python, with working knowledge of SAS and SQL; ability to develop, review, and support reproducible analyses, code quality, version control, and validated workflows.
- Working knowledge of CDISC standards, including SDTM, ADaM, controlled terminology, Define-XML concepts, and submission-oriented data expectations.
- Experience integrating, analyzing, and interpreting diverse data sources, including clinical trial, biomarker, real-world, external, imaging, digital health, or high-dimensional data as appropriate to assigned studies.
- Practical understanding of AI/ML and advanced analytics in regulated clinical development, including model development, validation, documentation, assumptions, bias considerations, and fit-for-purpose deployment.
- Knowledge of FDA, EMA, ICH-GCP, GxP, data privacy, inspection readiness, and traceability expectations relevant to clinical data and quantitative deliverables.
- Ability to develop clear analysis specifications, visualization approaches, documentation, and interpretation summaries suitable for scientific, operational, and study-team audiences.
- Familiarity with modern data platforms, reusable analytics workflows, automation, metadata-driven processes, and governed data standards.

### Behavioral Competencies
- Communicates quantitative findings clearly to scientific, operational, technical, and leadership audiences.
- Builds effective working relationships across study teams and functional partners.
- Demonstrates strong technical credibility, sound judgment, and collaborative problem-solving skills.
- Balances scientific rigor, quality, and timely delivery while proactively communicating risks and issues.
- Demonstrates accountability for assigned deliverables and commitment to reproducible, traceable, high-quality work.
- Embraces continuous learning and adoption of innovative analytical methods, automation, and AI-enabled approaches. Locations IND - Bengaluru - Research and Development Worker Type Employee Worker Sub-Type Regular Time Type Full time

## At a glance
- Posted by the employer: Oct 30, 2026
- First seen by OpenNash: Nov 1, 2026
- Last checked: Nov 1, 2026
- Listed for: 2 days
- Location: Bhartiya City, Bengaluru, Karnātaka, India
- Employment type: Full-time
- Pay: {'@type': 'MonetaryAmount', 'currency': 'USD', 'value': {'@type': 'QuantitativeValue', 'unitText': ''}}[Apply on Takeda Pharmaceutical’s careers site →](https://jobs.takeda.com/job/bengaluru/senior-manager-clinical-data-scientist/1113/102636742544)

## Hiring at Takeda Pharmaceutical
- Open jobs: 947
- New in the last 7 days: 151
- Tracked since: Jul 16, 2026

[All Takeda Pharmaceutical jobs](https://jobs.opennash.com/companies/takeda-pharmaceutical/) · [Weekly hiring report](/reports/hiring/)

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