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Job DescriptionObjective / 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.
LocationsIND - Bengaluru - Research and DevelopmentWorker TypeEmployeeWorker Sub-TypeRegularTime TypeFull timeSkills Required
- PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or a related field, with 5 or more years of relevant experience
- Master's degree in a relevant field with 7 or more years of relevant experience
- Experience supporting quantitative analyses and data science activities in pharmaceutical, biotechnology, healthcare research, or regulated clinical development environments
- Experience contributing to clinical development decisions through quantitative analysis, data interpretation, and communication of evidence
- Experience working on cross-functional study teams
- Experience working with clinical trial data and at least one additional data type, such as biomarker, real-world, external, imaging, digital health, or high-dimensional data
- Strong knowledge of clinical trial design, drug development, endpoints, estimands, biomarkers, and clinical decision analytics
- Strong foundation in statistics and quantitative methods, including longitudinal analysis, survival methods, causal reasoning, simulation, predictive modeling, and uncertainty communication
- Hands-on proficiency in R and/or Python
- 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
- Practical understanding of AI/ML and advanced analytics in regulated clinical development
- Knowledge of FDA, EMA, ICH-GCP, GxP, data privacy, inspection readiness, and traceability expectations
- Ability to develop analysis specifications, visualization approaches, documentation, and interpretation summaries for scientific, operational, and study-team audiences
- Familiarity with modern data platforms, reusable analytics workflows, automation, metadata-driven processes, and governed data standards
Takeda Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Takeda and has not been reviewed or approved by Takeda.
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Retirement Support — Employer-funded retirement is described as notably strong, combining a dollar-for-dollar 401(k) match with an additional company contribution that scales with age and service. Access to an employee stock purchase plan further supports long-term wealth building.
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Parental & Family Support — Paid bonding leave for all parents, substantial adoption/surrogacy reimbursement, and robust caregiver resources (backup care and Maven family-forming support) are emphasized as core strengths. These offerings create a comprehensive safety net for a range of family situations.
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Healthcare Strength — Multiple medical plan options (nationwide PPO/HSA and regional HMOs), employer HSA funding, and integrated mental-health and well-being programs signal depth in coverage. Preventive care is covered in-network, and plan choices by state expand access.
Takeda Insights
What We Do
For over 240 years, Takeda’s propensity to evolve has driven the next generation of innovation, and as a future-focused organization, we’re continuing to drive forward with endurance in our steadfast pursuit to achieve the best outcomes for our patients in a rapidly changing world. We have been preparing for this period of value creation by investing in data, digital and technology, and we’re proud of our employees and their commitment to turning groundbreaking ideas into life-changing impacts. Since our founding in Japan, integrity and putting patients first have been at the heart of our identity, and we will emerge ready for our future as one of the most trusted and science-driven digital biopharmaceutical companies. Join a team where your innovation impacts lives. Together, we’ll realize improved outcomes by improving data quality, enhancing launch execution and improving the patient journey. You’ll play a critical role in accelerating data collection and increasing accuracy across all parts of the business. Patients across the globe will benefit from access to treatments afforded by greater opportunities and efficiency in our research and development.
Why Work With Us
We connect to our history and Japanese heritage through everything we do to bring our purpose, values, vision, and imperatives to life. We are committed to bringing better health and a brighter future to patients. Being a part of Takeda means having the opportunity to be a part of something bigger than yourself.
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