GCM Evidence Generation Study Design & Execution Lead

Takeda Pharmaceutical Co.; Bengaluru; On-site; INR 900,000 - 1,300,000; Full time

Benefits offered by this job

Flexible work environment

Comprehensive Healthcare Insurance

Health & Wellness programs

Leaves and learning opportunities

Job summary

Takeda Pharmaceutical Co. in Bengaluru seeks a Statistics for Study Design and Execution Lead to establish the statistical capability for evidence generation study design and execution, including SAP development, programming, and RWD analysis.

You will provide hands-on design and programming support across the portfolio, enabling GCM teams to focus on scientific leadership while delivering analytical execution and methodology support.

Qualifications

• >3 years of related work experience in biostatistics, programming, or RWD analysis.
• Hands-on experience in biopharmaceutical or HEOR settings preferred.
• Experience supporting study design and execution in evidence generation.

Responsibilities

• Define and build statistical capability for study design and execution in Bengaluru.
• Develop programming standards, SAP shells, and QC checklists for reproducible statistical execution.
• Lead implementation of analytic plans and analyses for RWE studies across data sets.
• Design interventional and non-interventional studies, including sample size and power considerations.
• Document statistical planning decisions and rationale in study files per audit standards.
• Review protocols and synopses for statistical consistency and flag gaps.

Skills

Statistical programming

SAS

R

Python

Epidemiology

Education

MPH/PhD

Tools

SQL

SAS

R

Python

Job description

Job Description

Role Objectives:

As one of the first Statistics for Study Design and Execution Leads to join the Bengaluru GCM team, this role will establish the statistical capability required to support evidence generation study design and execution, covering statistical analysis plan development, programming, and real-world data analysis.

You will also provide hands-on statistical design and programming support across the evidence generation portfolio, enabling Global Evidence Generation study teams to focus on scientific leadership, endpoint strategy, and final study decisions while GCM delivers analytical execution, statistical planning documentation, and RWD methodology support.

Key Responsibilities

Initial Capability Build

• In the early build phase, work closely with Global Evidence Generation study leads and R&D statistical counterparts todocument the scope, standards, tools, templates, and handoff protocols that will govern statistical support activitiesperformed by the GCM going forward
• Develop programming standards, analysis templates, SAP shells, output shells, and QC checklists to support consistent andreproducible statistical execution as the team scales to two Leads
• Identify gaps in tool access, data system connectivity, or methodology guidance that need to be resolved before statisticalactivities can be fully transitioned to the GCM and flag these to the AD in a timely manner
• Support with development of SOPs and onboarding materials for all statistical programming and RWD analysis activities

Statistical Analysis Planning & Study Design Support

• Define appropriate statistical methods for RWD analyses and draft statistical analysis plans in collaboration with the subjectmatter expert to address evidence generation needs across the drug development life cycle
• Lead the implementation of analytic plans, execute analyses for RWE studies using appropriate data sets, as well asstandardized methods aligned withGxPfor insights, publications, regulatory and payer submissions
• Help design interventional and non-interventional (real world) studies, including (where appropriate) sample size calculationsand probability of success
• Develop and update HTA CTAP (clinical trial analysis plan), post-hoc analysis, and pre-specified analyses
• Work on responder analyses using machine learning
• Support external controls
• Review draft study protocols and synopses for statistical consistency and flag methodological gaps or assumptions requiringretained scientific review and resolution
• Document all statistical planning decisions, assumptions, and rationale in study files in line with repository and audit standards

Statistical Programming & Analysis Execution

• Generate analysis-ready datasets based on defined use cases and implement analytical methods producing guideline-compliant outputs — including tables, listings, and figures (TLFs) with all data preparation steps documented and traceablethroughout
• Write, validate, and execute programs in SAS, R, or Python per the Statistical Analysis Plan (SAP); conduct exploratory and adhoc analyses as requested, clearly documenting assumptions, scope, and limitations for each
• Support comparative effectiveness analyses, subgroup analyses, and health economic modeling by providing analyticalexecution and output production; identify and address common sources of bias in collaboration with the retained statisticalSME, testing appropriately for effect modifiers and documenting methodology choices and rationale
• Develop and validate statistical models that appropriately account for intercurrent events, competing risks, and multiplecomparisons; conduct sensitivity and robustness analyses as appropriate, flagging results and implications clearly for retainedscientific interpretation and reporting decisions
• Ensure all analytical steps are fully reproducible and auditable for regulatory, HTA, or other external review by maintainingcomplete programming logs, data lineage records, and version control across all programs, datasets, and outputs throughoutthe study lifecycle

Qualifications:

Experience: >3 years of related work experience; >2 years of experience in the biopharmaceutical industry; hands-on experience in biostatistics, statistical programming, or RWD analysis in a pharmaceutical, CRO, or HEOR context required; experience supporting study design and execution inan evidence generation, clinical development, or outcomes research setting strongly preferred

Technical skills:

• Knowledge of QC HTA-aligned analyses for payer/reimbursement evidence (e.g.PICO framework, Network meta-analyses, IPTW indirecttreatment comparisons).
• Knowledge of statistical analysis methods, experimental design and data processing softwarefor both clinical trials and non-interventionalstudies
• Expertise inSAS, R, SQL, Python, epidemiology, outcomes research, US secondary data sources, etc.
• Standards: CDISC,ADaM, PICO, HTA alignment
• Familiarity with and hands-on experience working on a variety of real-world data sources: Claims, EHR/EMR, registries, observational databases.
• Experience with real-world dataset management
• Ability to QC and review other statisticians/analysts’ outputs
• Statistical programming of clinical and real-world data for Phase IV trials, observational studies, and RWE research

Education: Master’s/PhD in public health, health outcomes, statistics, or epidemiology; experience with Python, SAS, or R

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.

Locations

IND - Bengaluru

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

Locations

IND - Bengaluru - Research and Development

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

Locations

IND - Bengaluru

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

Locations

IND - Bengaluru

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time