Senior Director, Statistical Innovation

Ipsen; Greater London; On-site; GBP 140,000 - 210,000; Full time

Job summary

Ipsen is seeking a Senior Director, Statistical Innovation to lead innovative methodology across its R&D portfolio. You will head a 3–5 person team delivering adaptive and Bayesian trial designs, external controls, digital twins, and predictive analytics to strengthen development decisions and portfolio value.

You will collaborate across Biometry, Clinical Development, Regulatory Affairs, and Data Science to ensure rigour, feasibility, and regulatory acceptability, while building reusable tools

Qualifications

• 10+ years in pharmaceutical/biotech quantitative roles with advanced degrees
• Expertise in innovative trial design, simulation, Bayesian methods, and data mining
• Strong programming and modern modelling capabilities; reproducible workflows

Responsibilities

• Provide strategic input to innovative trial designs including adaptive and master protocol approaches
• Lead a 3–5 person quantitative team with accountability for quality and capability building
• Develop simulation frameworks to optimize sample size and decision rules
• Lead advanced modelling for disease progression, dose/regimen, patient journeys, digital twins and external controls
• Communicate complex statistical outputs to senior stakeholders and ensure regulatory acceptability

Skills

Leadership

Strategic thinking

Statistical analysis

Communication

Education

MS/MSc or PhD in statistics or mathematics

Tools

R

Python

SAS

Job description

WHAT - Summary & Purpose Of The Position

The Senior Director, Statistical Innovation leads innovative methodology, advanced modelling, and data-driven decision support across Ipsen’s R&D portfolio, strengthening development strategy through design, simulation, and predictive analytics.

The role leads a specialist team of 3 to 5 quantitative experts supporting innovative trial design, advanced modelling, digital twins, virtual controls, patient journey modelling, and data mining to improve development decisions, study efficiency, population selection, and portfolio value.

Working closely with Clinical Development, Biostatistics, Statistical Programming, Translational Medicine, Biomarkers, Regulatory Affairs, Data Science, Business Development, Asset Teams, and Biometry Leadership, the role ensures innovative statistical approaches are scientifically rigorous, operationally feasible, and aligned with regulatory, clinical, and portfolio decision needs.

The role builds a sustainable statistical innovation capability through high-value use cases, standards, reusable tools, external engagement, specialist talent development, and broader Biometry and asset-team upskilling.

WHAT - Main Responsibilities & Technical Competencies

• 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, 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.

HOW - Behavioural Competencies Required

Competency Competency Behavioural Markers Explanation of Choice

Ensures Accountability

• Ensures single accountable referents per task/project/outcome (independent of organizational context or multi-team projects)
• Builds and anchors an environment where people have the skills and habits to ask for clarification when accountabilities are unclear
• Consults/seeks relevant stakeholder views/expertise and coaches/ensures decisions are made by consent vs. consensus
• Takes personal accountability for decisions, actions, successes and failures, and fosters the same for others
• Follows through on commitment and makes sure others do the same

Owns innovation strategy, methodology quality, priorities, and decision-ready outputs.

Develops/Coaches Talent

• Able to identify and align career goals, and blend organizational objectives into a cohesive development plan for self and team
• Able to coach
• Provides structured, actionable, regular and directional feedback and acts as a coach to empower people to own their own growth/development
• Prepares their own succession plans
• Displays a radically human-centered mindset; puts people first; focuses on doing good
• Demonstrates ability to build team effectiveness

Leads a specialist team and builds broader Biometry and asset-team capability.

Drive Vision and Strategy

• Paints a compelling picture of the vision (future status quo) and strategy that motivates others to action Sets direction for innovation, modelling, digital twins, and analytics to increase PTRS and portfolio value.

Manage Complexity

• Identifies contradictory information/demands/inputs to effectively solve problems
• Develops and evaluates alternative scenario and solutions
• Able to identify what truly matters and ruthlessly focus/ prioritize on making decisions with real impact Navigates complex scientific, regulatory, data, modelling, and operational decisions.

Communicates Effectively

• Asks open questions and digs deeper; shows care and respect for different perspectives (both verbally and non-verbally) and able to relate to other points of view
• Communicates transparently, tells it how it is while keeping the communication respectful
• Builds clear and crisp messages with structure and focus, uses visual communication and storytelling to make the message easy to digest and connect with the outcomes
• Demonstrates gravitas

Turns complex quantitative concepts into clear recommendations for teams, leaders, and stakeholders.

HOW - Knowledge & Experience

Knowledge & Experience (essential):

• 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 to support evidence generation and key clinical development, population, dose/regimen, endpoint, and portfolio decisions.
• 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, with the ability to guide reproducible modelling and simulation workflows.
• Proven ability to influence global cross-functional teams and communicate complex methods, assumptions, uncertainty, limitations, and decisions clearly.

Knowledge & Experience (preferred)

• Experience with advanced data science methods, including digital twins, virtual/external controls, Bayesian borrowing, causal inference, patient journeys, machine learning.
• Experience in oncology, rare disease, neuroscience drug development.
• Track record of scientific publications, conference presentations, external collaborations, or contributions to industry working groups in statistical innovation or quantitative methods.

Education / Certifications (essential)

• MS/MSc or PhD in statistics, mathematics or another relevant quantitative discipline.

Language(s) (essential)

• Fluent in English, with e