Associate Director, Clinical Data Scientist Statistics

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Objective / 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 Takedas 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. Were not just transforming our company; were 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

Employee

Regular

Full time