Director, Digital Quantitative Sciences

ROLE SUMMARY

The Director, Digital Quantitative Sciences is responsible for ensuring sound statistical thinking and methods are utilized in the discovery and development of novel digital and imaging endpoints and for bringing the principles of objective decision-making into the development, validation, and implementation of industry-leading digital health technology and imaging programs for incorporation into clinical trials across Pfizer’s portfolio. The Director is an integral member of a matrixed team, which develops and employs computational and statistical approaches to discover and validate digital and imaging endpoints and biomarkers. The Director must possess the ability to plan, direct and coordinate a variety of specialized and complex projects, must have knowledge of study design of experiments, data management and programming tools, and ability to interpret results from clinical studies. The Director should have ability to roll out new initiatives and assists in strategic planning. The Director should be a person of vision, should stay current on new developments and technological advancement in statistics and AI/ML methodologies. The candidate should be highly motivated and should possess excellent written and verbal communication skills.

This role sits in Pfizer’s AI/ML, Quantitative & Digital Sciences (AQDS) team within Global Biometrics and Data Management, Pfizer Research & Development, leveraging multi-modal data, digital measures, and the power of quantitative science to inform trial designs, support clinical and regulatory strategy and build patient-centric health solutions. The successful candidate will partner closely with Translational Clinical Sciences, Biomeasures, Endpoints & Study Technology to develop novel measures that advance drug development.

ROLE RESPONSIBILITIES

• Demonstrate leadership experience and ability to lead teams and mentor colleagues.

• Lead novel statistical methodology projects with internal and external partners to advance the development of digital and imaging endpoints for use in clinical trials.

• Serve as the lead statistician on clinical trials incorporating novel AI/ML-based technologies and novel study designs such as decentralized clinical trials.

• Bring innovative statistical thinking and methods to help drive data-driven drug discovery and development employing modern methods such as machine learning/AI, longitudinal and time series methods, multivariate and functional data analysis approaches, and Bayesian methodologies.

• Collaborate with interdisciplinary teams including clinicians, data scientists and data managers to develop, validate and deploy algorithms and analysis pipelines to derive digital endpoints for use in clinical trials.

• Ensure rigorous approaches are taken and good scientific practices are followed: excellent statistical methods utilized and documented in protocols, analysis plans and manuscripts, and assay methods are appropriately blinded, randomized and designed to meet clear study objectives.

• Provide statistical input and leadership to determine strategy and deliver results in a timely and high-quality manner. Ensure that all statistics activities are conducted in compliance with relevant regulatory requirements and Pfizer standards.

• Interact withinternal and external experts to assure sound quantitative approaches are applied to the collection and analysis of a wide variety of data types, including digital health technology data, imaging, and blood-based biomarkers.

• Provide planning and communication of statistical analyses, data presentations and scientific reports, including clinical trial results, exploratory analyses and analyses that synthesize results across studies, support for publication activities, scientific presentations, and regulatory interactions.

QUALIFICATIONS

Basic qualifications

• PhD in Statistics, Biostatistics or in quantitative discipline such as Physics, Applied Mathematics, Bioengineering, Electrical Engineering coupled with high level of statistical expertise and 7 years or more of industrial or similar experience, or Masters in the same fields and 9 years or more of industrial or similar experience.

• Research experience with mathematical/statistical modeling using complex data.

Technical Skills

• Fluency in R and SAS programming

• Programming in Python

• Experience in clinical statistics supporting early / late-stage clinical development and/or real-world evidence studies

• Expert level knowledge of machine learning algorithms, feature selection and optimization.

• Experience analyzing digita