United States - Massachusetts - Cambridge We're in relentless pursuit of breakthroughs that change patients' lives. We innovate every day to make the world a healthier place.
To fully realize Pfizer's purpose – Breakthroughs that change patients' lives – we have established a clear set of expectations regarding "what" we need to achieve for patients and "how" we will go about achieving those goals.
Pfizer Research & Development serves as the beating heart of Pfizer's trailblazing product pipeline, the essence of our mission to bring life-changing medicines to the world.
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 with internal 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 programmingProgramming in PythonExperience in clinical statistics supporting early / late-stage clinical development and/or real-world evidence studiesExpert level knowledge of machine learning algorithms, feature selection and optimization.Experience analyzing digital health technologies data, such as accelerometry, wearable devices and mobile app data.Strong background in experimental design and statistical analysis including good understanding of inference and probability, competence in contemporary linear and predictive modeling including (longitudinal) mixed models, nonlinear regression, and predictive modeling.Genuine interest in biology and pharmaceutical development, with the attitude of self-directed scientist; demonstrated ability to multitask.Outstanding communication skills; Ability to explain statistical and modeling concepts to non-experts.Demonstrated ability to work effectively independently and as a part of a team. Preferred Qualifications Experience leading teams/mentoring colleagues Technical Skills Prior use of cloud computing tools, e.g., AWSKnowledge of MATLABKnowledge of adaptive clinical trial designs and/or cluster randomized trials is an advantage.Experience analyzing large scale imaging datasets.Knowledge of methods of signal processing including electrophysiological data analysis.Knowledge of functional data analysis approaches and Bayesian methods.Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact. Work Location Assignment: On premise with relocation support available.
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