Description

The Opportunity

We are seeking a driven and innovative Lead Statistician to serve as the technical authority for statistical strategy and delivery within our Orthopedic Reconstruction & Robotics portfolio. This is a high-impact leadership role where you will directly support complex studies and provide program-level guidance across all statistical activities.

From study design and simulation-based planning to the interpretation of complex datasets, you will ensure scientific rigor and quality across the business unit. As a mentor and thought partner, you will champion innovative methodologies (such as Bayesian frameworks and causal inference) and ensure our evidence generation remains at the forefront of global clinical and regulatory standards.

Core Responsibilities Statistical Leadership and Strategy

• Technical Authority: Serve as the lead statistical voice for the Orthopedic Reconstruction & Robotics portfolio, providing strategic input for clinical evidence generation.
• Innovation Champion: Promote the use of innovative methodologies and study designs, ensuring consistency and scientific rigor across all programs.
• Mentorship: Coach and conduct technical reviews for the "Statistics Pod," fostering professional growth and execution excellence in a matrixed environment.
• Cross-Functional Partnership: Align statistical approaches with regulatory expectations, scientific best practices, and broader business priorities.

Study Design and Analysis

• Advanced Planning: Provide expert guidance on sample-size estimation, randomization, adaptive/hybrid designs, and simulation-based planning.
• Robust Frameworks: Collaborate with Clinical Operations and Strategy to define study types, endpoints, and fit for regulatory submission.
• Complex Analysis: Oversee the conduct of advanced analyses, including survival analysis, mixed-effects models, and propensity scores.
• Tool Modernization: Lead the effective use of SAS, R, and emerging analytical tools, ensuring deliverables meet modern reproducibility standards.

Data Quality and Interpretation

• Technical Oversight: Partner with Data Management and Programming to oversee data cleaning, derivation, and integration.
• Insight Translation: Translate complex findings into actionable insights for clinical, regulatory, and executive stakeholders.
• Reporting: Lead statistical content for Clinical Study Reports (CSRs), regulatory submissions, and high-impact publications.

Continuous Improvement

• Regulatory Awareness: Maintain a deep understanding of emerging statistical methodologies and regulatory guidance relevant to medical device research.
• Operational Excellence: Support the development of harmonized SOPs and governance frameworks across Global Clinical and Medical Affairs.

Qualifications

Education

• Minimum: Master's degree in Statistics, Biostatistics, Applied Mathematics, or a related quantitative discipline.
• Preferred: Ph.D. in a related field.

Experience

• Applied Experience: Minimum of 5 years (with a Master's) or 2 years (with a Ph.D.) as a clinical statistician in an academic or industry setting.
• Leadership: Proven track record of leading statistical activities and influencing teams within a matrixed environment.
• Regulatory Knowledge: Strong understanding of clinical research standards (e.g., FDA, ISO 14155).
• Technical Proficiency: Advanced expertise in statistical programming using SAS and R.

Key Competencies

• Lifelong Learner: A true passion for innovation and a strong theoretical foundation in mathematics.
• Communicator: Ability to confidently explain complex statistical reasoning to non-statistical audiences.
• Mentor: Proven ability to inspire and elevate the technical capabilities of junior staff.

Preferred Skills & Domain Expertise

• Experience with Bayesian approaches, causal inference frameworks, and simulation.
• Familiarity with CDISC standards, version control (Git), and modern data science collaboration tools.
• Domain knowledge in medical device robotics, AI-SaMD, or orthopedic reconstruction.
• Experience with long-term (up to 10 years) follow-up studies and clinical registry data analysis.