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Job DescriptionObjective / Purpose:
Serve as an Associate Director-level clinical data science leader within Data & Quantitative Sciences, translating complex clinical, biomarker, and external data into actionable evidence that informs clinical development decisions.
Lead fit-for-purpose statistical, data science, and advanced analytics approaches across assigned studies, assets, or specialty areas, including exploratory analysis, predictive modeling, simulation, and integrated data review.
Partner cross-functionally with Clinical, Clinical Pharmacology, PSPV, Clinical Data Management, Translational Sciences, Regulatory, Clinical Operations, and external partners to ensure high-quality, traceable, analysis and submission-ready data and decision-ready insights.
Advance modern ways of working by applying AI/ML, automation, reusable analytics workflows, and governed data standards while maintaining scientific rigor, regulatory awareness, and patient-focused decision making.
Accountabilities:
Design and/or execute quantitative analyses using clinical trial data, biomarkers, real-world data, external data, and other relevant sources to generate interpretable insights for study teams and governance forums.
Apply appropriate statistical, machine learning, simulation, and visualization methods to support patient-level prediction, endpoint interpretation, risk assessment, scenario planning, and evidence generation.
Perform end-to-end data analyses, from hypotheses formulation, experimental design, writing analysis plans, data cleaning, executing analysis, and preparing reports and documentation.
Provide or identify internal and external statistical expertise and capacity to support development activities.
Lead clinical data science strategy and delivery for one or more studies, assets, or capability areas, ensuring alignment with development objectives, timelines, quality expectations, and stakeholder needs.
Provide scientific and technical oversight of internal and external delivery partners, including review of analysis plans, specifications, code, outputs, data visualization, and interpretation of findings.
Identify, communicate, and mitigate risks related to data quality, analytic assumptions, vendor delivery, timelines, reproducibility, and regulatory acceptability of data science outputs.
Assess, communicate and propose solutions for internal, external resource and/or quality issues that may impact deliverables/timeline at the program level.
Partner with Clinical Pharmacology PSPV, Translational Sciences, Clinical Data Management, Regulatory, and platform teams to ensure that CDISC, submission, and downstream quantitative decision-making needs are built into study setup, data review, and reporting processes.
Define requirements for model-ready datasets and analytics-ready data flows, including variable derivations, data quality expectations, lineage, traceability, metadata, and documentation sufficient for regulated clinical development use.
Mentor junior colleagues or delivery partners in clinical data science methods, reproducible analytic practices, technical problem solving, and effective communication of quantitative insights.
Increase the external recognition of Takeda’s data science work by participating in conferences, publishing work and developing external collaborations.
Drive continuous improvement in clinical data science practices through reusable code, standards, training, mentoring, automation, AI-enabled workflow improvements, and adoption of industry best practices.
Education & Competencies (Technical and Behavioral):
Education / Experience
PhD in statistics, biostatistics, data science, applied mathematics, physics, epidemiology, biomedical engineering, computer science, quantitative sciences, or related field with 5+ years of relevant experience; or MS with 8+ years of relevant experience. Equivalent combinations should be reviewed with HR.
Significant experience in clinical development within the pharmaceutical, biotechnology, or healthcare research environment, with demonstrated ability to influence cross-functional decisions at study, asset, or functional level.
Experience providing technical leadership, matrix leadership, vendor oversight, and/or mentorship of junior colleagues or delivery partners.
Highest-priority Technical Skills
Advanced 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 uncertainty communication.
Experience integrating and interpreting diverse data sources, including clinical trial, biomarker, real-world, external, imaging, digital health, or other high-dimensional data as appropriate to the portfolio.
Practical understanding of AI/ML and advanced analytics in regulated clinical development, including model development, validation, documentation, bias/assumption assessment, and fit-for-purpose deployment.
Hands-on proficiency in SAS, with working knowledge of R and/or Python and SQL; ability to review and guide reproducible analyses, code quality, version control, and validated workflows.
Ability to work independently on complicated datasets, including all aspects of data analysis (data cleaning, algorithm development, statistical analysis, and documentation).
Working knowledge of CDISC standards, including SDTM, ADaM, controlled terminology, Define-XML concepts, and submission-oriented data expectations.
Knowledge of FDA, EMA, ICH-GCP, GxP, data privacy, inspection readiness, and traceability expectations relevant to clinical data and quantitative deliverables.
A working knowledge of UNIX operating systems is preferred, ideally with experience in high-performance computing environments.
Behavioral Competencies
Communicates complex quantitative findings clearly to scientific, operational, technical, and senior leadership audiences.
Influences across functions without relying on direct authority; builds trusted partnerships with clinical, statistical, programming, data management, regulatory, technology, and vendor stakeholders.
Balances scientific rigor, speed, quality, and pragmatic delivery; proactively escalates risks with options and recommendations.
Demonstrates enterprise mindset, curiosity, continuous improvement, and commitment to developing others and advancing modern clinical data science capabilities.
Benefits
It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are:
Competitive Salary + Performance Annual Bonus
Flexible work environment, including hybrid working
Comprehensive Healthcare Insurance Plans for self, spouse, and children
Group Term Life Insurance and Group Accident Insurance programs
Health & Wellness programs including annual health screening, weekly health sessions for employees.
Employee Assistance Program
5 days of leave every year for Voluntary Service in addition to Humanitarian Leaves
Broad Variety of learning platforms
Diversity, Equity, and Inclusion Programs
No Meeting Days
Reimbursements – Home Internet & Mobile Phone
Employee Referral Program
Leaves – Paternity Leave (4 Weeks) , Maternity Leave (up to 26 weeks), Bereavement Leave (5 days)
About ICC in Takeda
Takeda is leading a digital revolution. We’re not just transforming our company; we’re improving the lives of millions of patients who rely on our medicines every day.
As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization.
IND - Bengaluru
Worker TypeEmployee
Worker Sub-TypeRegular
Time TypeFull time
LocationsIND - Bengaluru - Research and DevelopmentWorker TypeEmployeeWorker Sub-TypeRegularTime TypeFull timeSkills Required
- PhD in statistics, biostatistics, data science, applied mathematics, physics, epidemiology, biomedical engineering, computer science, quantitative sciences, or related field with 5+ years of relevant experience
- Alternatively, an MS in a relevant field with 8+ years of relevant experience
- Significant clinical development experience within pharmaceutical, biotechnology, or healthcare research environments
- Experience influencing cross-functional decisions at the study, asset, or functional level
- Experience providing technical leadership, matrix leadership, vendor oversight, or mentorship
- Advanced knowledge of clinical trial design, drug development, endpoints, estimands, biomarkers, and clinical decision analytics
- Strong statistical and quantitative methods expertise, including longitudinal analysis, survival methods, causal reasoning, simulation, predictive modeling, and uncertainty communication
- Experience integrating clinical trial, biomarker, real-world, external, imaging, digital health, or other high-dimensional data
- Practical understanding of AI/ML and advanced analytics in regulated clinical development
- Hands-on proficiency in SAS
- Working knowledge of R and/or Python and SQL
- Ability to independently perform data cleaning, algorithm development, statistical analysis, and documentation
- Working knowledge of CDISC standards, including SDTM, ADaM, controlled terminology, and Define-XML concepts
- Knowledge of FDA, EMA, ICH-GCP, GxP, data privacy, inspection readiness, and traceability expectations
- Working knowledge of UNIX operating systems and high-performance computing environments
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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