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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates deep expertise in innovative trial design, advanced modelling, and predictive analytics, with strong programming skills in R, Python, or SAS. Proven ability to lead specialist quantitative teams and communicate complex statistical outputs effectively to support strategic decision-making.
Highest-signal resume keywords
Innovative Trial DesignAdvanced ModellingPredictive AnalyticsStatistical Programming in R, Python, SASTeam Leadership and Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Innovative Trial DesignAdvanced ModellingPredictive AnalyticsData MiningSimulation FrameworksBayesian MethodsCausal InferenceStatistical ComputingEstimation TechniquesRegulatory Compliance
Soft Skills
Stakeholder ManagementCoachingCommunicationInfluencing
Tools & Technologies
RPythonSASDigital TwinsMachine Learning
Certifications & Qualifications
PhD in StatisticsMS/MSc in Statistics or Mathematics
Industry Keywords
PharmaceuticalBiotechnologyCROClinical DevelopmentOncologyRare DiseaseNeuroscienceQuantitative MethodsStatistical InnovationExternal Controls
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Lead Statistical Innovation within Biometry, accountable for strategy, priorities, quality, and capability building across a 3 to 5 person specialist team
- Provide strategic input to innovative trial designs, including adaptive, Bayesian, enrichment, external-control, master protocol, interim, simulation, and endpoint strategies
- Develop simulation frameworks to assess operating characteristics, optimize sample size, test decision rules, and support go/no-go decisions
- Lead advanced modelling across clinical development and evidence generation, including disease progression, dose/regimen, patient journeys, digital twins, and virtual controls
- Drive data mining and predictive modelling to identify response predictors, heterogeneity, enrichment opportunities, prognostic factors, and patient subgroups
- Advise on external controls, digital twins, Bayesian borrowing, historical data, and RWE, addressing bias, confounding, estimands, data quality, regulatory acceptability, and interpretability
- Identify and implement emerging statistical and modelling approaches for high-impact Ipsen use cases
- Establish standards, reusable code, templates, documentation, QC expectations, and governance for innovation deliverables
- Lead and develop statisticians through prioritization, coaching, recruitment input, and succession planning
- Work with Biostatistics and Statistical Programming to ensure methods are feasible, robust, reproducible, and submission-ready
- Represent Biometry in governance, asset reviews, development planning, due diligence, and external scientific discussions
- Build external networks with academics, consortia, and industry groups to maintain methodological currency
- Communicate complex statistical and modelling outputs clearly to support senior decisions, development strategy, and portfolio prioritization
Requirements
What you’ll need- 10+ years of pharmaceutical, biotechnology, CRO, academic, or related quantitative experience with a PhD, or equivalent experience with an MS/MSc
- Deep expertise in innovative trial design, advanced modelling, simulation, predictive analytics, and data mining
- Strong understanding of clinical development, regulatory expectations, estimands, missing data, multiplicity, bias and confounding
- Experience leading specialist quantitative teams, including prioritization, coaching, capability development, delivery oversight, stakeholder management, and succession planning
- Strong programming capability in R, Python, SAS, or equivalent statistical computing environments
- Proven ability to influence global cross-functional teams and communicate complex methods, assumptions, uncertainty, limitations, and decisions clearly
- MS/MSc or PhD in statistics, mathematics or another relevant quantitative discipline
- Fluent in English
- Preferred: experience with advanced data science methods, including digital twins, virtual/external controls, Bayesian borrowing, causal inference, patient journeys, and machine learning
- Preferred: experience in oncology, rare disease, or neuroscience drug development
- Preferred: track record of scientific publications, conference presentations, external collaborations, or contributions to industry working groups in statistical innovation or quantitative methods
Benefits
Comp & perks- Inclusion and equal opportunities
- Application adjustments or support available during the recruitment process
- Application support information handled with care and without affecting the application outcome