Statistical Science Lead, Solid Tumor

Responsibilities

• Serve as the compound-level statistical lead for solid tumor oncology, responsible for end-to-end quantitative strategy supporting clinical development, evidence generation, and regulatory/payer interactions.
• Lead development of integrated statistical strategies across all relevant study types and functions (e.g., phase 1b/2 signal-seeking, pivotal, exploratory, RWE, post-marketing).
• Align statistical and analytical approaches with the target product profile (TPP), development strategy, and external evidence needs.
• Lead and coordinate statistical and analytics contributions from a broad QSEG team, including:
• Clinical trial biostatisticians
• Exploratory oncology statisticians (e.g., tumor burden modeling, subgroup/signal detection)
• Medical Affairs statisticians
• Statistical programmers
• Biomarker/statistical genetics experts in oncology
• RWE analysts/statistical epidemiologists
• Safety/PV statisticians
• Advanced analytics and modeling specialists
• Ensure scientific alignment, quality, and integration across all statistical contributions at the compound level.
• Represent Astellas on all statistical matters in global regulatory interactions (e.g., FDA, EMA, PMDA).
• Guide preparation of statistical content for regulatory submissions, briefing packages, and health technology assessment (HTA) dossiers.
• Lead the development of statistical components of payer evidence strategies, including indirect comparisons and external control methodologies.
• Promote oncology-appropriate innovations, including Bayesian designs, adaptive trial designs, external controls, tumor-agnostic approaches, and AI/ML tools to enhance study design and signal detection.
• Support rapid development decisions in Solid Tumor trials through exploratory data analysis, modeling, and simulation.
• Integrate clinical, biomarker, safety, and real-world evidence to drive cohesive, data-driven development and access strategies.
• Mentor statisticians and analytics professionals across QSEG, supporting both scientific development and career growth.
• Share knowledge and best practices across study teams and therapeutic areas.
• Contribute to internal training, methodology development, and talent pipeline initiatives.
• Participate in global asset governance and development team meetings, influencing decisions with rigorous statistical insight.
• Collaborate with Clinical Development, Medical Affairs, Regulatory, Market Access, and Commercial to ensure alignment on evidence planning.
• Lead or contribute to internal initiatives, including standardization efforts, methodology forums, and innovation networks.

Qualifications

• Advanced degree (PhD, MD, MBA, or equivalent) in Oncology, Life Sciences, or a related field.
• Minimum 8 years of experience in pharmaceutical R&D, external innovation, academic collaboration, or scientific partnering.
• Strong understanding of oncology drug discovery, translational science, and modality platforms (e.g., next gen ADCs, engineered biologics, engineered small molecules).
• Proven ability to engage with scientific leaders and navigate early-stage biotech and academic ecosystems.
• Excellent communication skills with the ability to synthesize complex scientific information into strategic insights.
• Prior experience in academic liaison, external innovation, or strategic scouting in pharma/biotech or venture ecosystems.
• Familiarity with CI platforms, digital literature monitoring tools, and academic/biotech databases.
• A strong network in academia or biotech focused on oncology.
• Experience in competitive intelligence, scientific scouting, or innovation strategy within oncology.
• Familiarity with academic-industry collaboration models and consortia-based innovation.
• High digital literacy and comfort with landscape analytics, scientific intelligence platforms, and conference tracking tools.
• PhD (or MSc with equivalent experience) in Biostatistics, Statistics, or a related quantitative discipline.
• Minimum of 10 years of experience in oncology clinical development, with proven leadership in statistical strategy and regulatory submissions.
• Demonstrated experience leading statistical contributions at the compound level, including regulatory engagement and cross-functional integration.
• Broad expertise across clinical trial design, exploratory oncology analytics, biomarker evaluation, RWE, and post-marketing study support.
• Broad expertise across clinical trial statistics, exploratory statistics, Medical Affairs statistics, biomarker statistics, safety/PV statistics, real-world evidence (RWE) analytics, and statistical programming.
• Strong understanding of the drug development lifecycle, regulatory requirements, and evidence generation for both approval and market access.
• Ability to lead and influence cross-functional, global teams within a matrix environment.
• Strong communication, collaboration, and stakeholder engagement skills across both technical and non-technical audiences.
• Proficiency in statistical software (e.g., SAS, R) and familiarity with simulation tools and modern statistical methods.