Biostatistics and Data Sciences (BDS) is a global organization with more than 350 employees within the Human Pharma Business Unit of Boehringer Ingelheim. In close collaboration with functions across the company and with external partners, we integrate advanced statistical methodology and modern data science capabilities with deep scientific and business understanding. Together we support robust evidence generation and smart, timely, and confident decision‑making throughout the drug development lifecycle. As we continue to transform BDS into a modern data science organization in late‑phase clinical development, built to succeed in an environment of rapid and continuous change, we aim to further strengthen our Therapeutic Area and Methodology Statistics (TAM STAT) function. In particular, we are expanding the capability cluster that supports methodology and decision science. We are therefore seeking a colleague who can drive user‑centric innovation in trial clinical trial methodology and improve its accessibility for our clinical development teams through consultancy and effective solutions.. As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies' success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees.

Collaborate with statisticians across therapeutic areas and provide expert statistical‑methodological guidance, consultancy, and problem‑solving support for complex challenges in clinical development, with a focus on phase II and III clinical trials.

• Assess, develop, and recommend innovative and advanced statistical methods that enhance the efficiency, robustness, and interpretability of clinical trial design, analysis, and decision making.
• Prototype methodological approaches and develop high‑quality, ready‑to‑use toolkits to enable their adoption across clinical programs.
• Lead and support statisticians in applying these methods to their studies and development plans.
• Communicate and illustrate complex statistical concepts clearly and quantitatively to diverse stakeholders, including clinical trial teams, governance bodies, external collaborators, and regulatory agencies.
• Deliver statistical‑methodological training for both statisticians and non‑statisticians, supporting capability building across the organization.
• Lead or contribute to cross‑functional working groups, and actively engage in industry initiatives and collaborations with academic partners and methodological experts.
• Mentor and guide colleagues within the statistical community.
• Provide scientific and technical direction to interns, students, and early‑career statisticians and support their development.
• Planning and directing statistical‑methodological consultancy for complex, partially defined problems with substantial uncertainty in clinical trials.
• Additional tasks & responsibilities for Senior Principal:
• Identifying high‑impact, innovative statistical methods and initiating their evaluation and implementation within the organization.
• Designing statistical‑methodological training activities and contributing actively to internal learning communities.
• Leading internal and external working groups and representing the statistical‑methodology function in cross‑company or industry initiatives.

• PhD in Statistics, Mathematics, or a closely related quantitative field is desirable; a Master’s degree with substantial experience as a statistician in drug development within an international environment is also considered.
• At least three years of experience as a statistician in the pharmaceutical industry or a regulatory agency would be a plus.
• Sound understanding of clinical drug development and of the statistical principles that guide evidence generation in late‑phase trials, together with solid knowledge of the relevant international regulatory guidance.
• Demonstrated hands‑on experience in statistical consultancy for clinical development teams, including the design, analysis, and interpretation of complex or innovative clinical studies.
• Proven track record in developing, extending, implementing, and delivering training on advanced statistical methods relevant to clinical development.
• Proficiency in statistical software (preferably R).
• Experience in statistical simulation using high performance computing environments or translating statistical methodology into robust, ready‑to‑use software tools is an advantage.
• Knowledge of modern data visualization and data‑driven communication concepts is beneficial.
• Strong interpersonal and communication skills with the ability to challenge ideas constructively and engage in scientific debate.
• Demonstrated ability to work effectively in global, cross‑functional environments.
• Fluency in written and spoken English.
• Additional requirements for a Senior Principal Position:
• Extensive and mature understanding of clinical development, covering strategic, methodological and operational dimensions.
• Compensation:
• Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees.

Strong scientific background in one or more areas such as: design of experiments, estimands, group-sequential and adaptive designs, multiple testing, longitudinal data analysis, handling of missing data, Bayesian borrowing, probability of success/assurance, go/no-go decision frameworks, or portfolio level decision making.

In‑depth expertise in more than two statistical domains, such as: design of experiments, estimands, group-sequential and adaptive designs, multiple testing, longitudinal data analysis, handling of missing data, Bayesian borrowing, probability of success/assurance, go/no-go decision frameworks, or portfolio-level decision making.