Statistical Innovation Lead

Bayer•Cambridge, MA

About The Position

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice. Statistical Innovation Lead PURPOSE: The Statistical Innovation Lead in Clinical Statistics and Analytics – Statistical Innovation will leverage advanced statistical methodology to optimize clinical trial designs and data analytics across different stages of drug development. The incumbent will innovate through the development and application of novel study designs, advanced modelling and simulation techniques including Bayesian methods and predictive analytics and implement effective strategies to improve end-to-end efficiencies during drug development. Provides hands-on implementation of innovative approaches, through direct interactions with clinical project teams and other relevant functional clusters, to influence decision-making processes and support quantitative decision-making during drug development and/or life-cycle management of Bayer products. LOCATION: Whippany, NJ or Cambridge, MA SCOPE: Global: responsible for all innovative statistical, technical and operational aspects related to global studies and projects in drug development, interaction with global authorities TASKS AND OUTPUTS: In the spirit of a DSO (Dynamic Shared Ownership) environment, the major tasks and responsibilities listed below are those that are supported and achieved by the Statistical Innovation group, not necessarily each individual. Member of expertise hub and resource to support Study/Project Statisticians and clinical project teams to develop and participate in hands-on implementation of innovative trial designs and advanced statistical methodology across the drug development portfolio. Addresses complex challenges in drug development and life-cycle management through the use of advanced modeling and/or simulation techniques, including Bayesian methods and predictive analytics, to optimize clinical trial designs and data analytics. Applies innovative approaches to utilize various data sources to improve clinical study designs, enhance data insights and gain end-to-end efficiencies for agile data-driven decision-making. Drives the development and implementation of novel study designs, including adaptive designs and Bayesian model-based designs, and advanced data analytic tools (R-Shiny apps/statistical software tools) using state-of-art statistical methodology in accordance with regulatory requirements. Provides innovative statistical and methodological approaches to specialized complex challenges related to optimizing clinical trial designs, leverage artificial intelligence and machine learning, enhance predictive analytics and causal inference and advanced statistical methods to support real-world evidence and personalize medicine strategies. Represents the Statistical Innovation group with respect to statistical/innovative aspects of clinical development programs and products to internal and external stakeholders. Maintains an external network of professional societies through active conference participation, academic institutions/experts, KOLs, industry wide working groups and Health Authorities to be recognized at the forefront of statistical innovation and new industry trends in clinical trial design and excellence in data analytics. Provides training to Statisticians, clinical project teams and internal stakeholders on advanced statistical methods and novel study designs for knowledge sharing, implementation and large-scale adoption.

Requirements

University degree (PhD preferred) in a relevant field such as Biostatistics, Statistics or Mathematics, or related field
At least eight years as a Statistician and/or applied quantitative methods role for decision-making with significant time spent in pharmaceutical drug development
High level of expertise in applying innovative statistical methodology to a broad range of study designs including adaptive designs, advanced modeling and simulation techniques with working knowledge of Bayesian methods, and effective strategies for operational efficiencies in drug development
Embrace and role model the VACC (Visionary/Architect/Catalyst/Coach) behaviors in leadership, as well as mentoring/coaching capabilities across diverse cultural environments, in a DSO (Dynamic Shared Ownership) environment
Outstanding interpersonal, leadership and communication skills; fluent English skills and strong presentation skills
Ability to work independently as well as collaboratively, as required
Thorough knowledge of the pharmaceutical industry and understanding of the clinical drug development process and/or life-cycle management, including in-depth knowledge of regulatory requirements governing clinical trial data (e.g. FDA regulations, ICH guidelines)
Excellent knowledge of statistical programming languages (including SAS and/or R, Python) and/or Bayesian software (including BUGS, JAGS and/or Stan) including knowledge of/experience building RShiny applications
Demonstrated leadership skills in (matrix) leading teams of Statisticians and/or representatives from other functional clusters
Broad expertise in multiple fields relevant for clinical development
High affinity to internal and external collaboration, including commitment towards external visibility, strong scientific publication record.

Responsibilities

Member of expertise hub and resource to support Study/Project Statisticians and clinical project teams to develop and participate in hands-on implementation of innovative trial designs and advanced statistical methodology across the drug development portfolio.
Addresses complex challenges in drug development and life-cycle management through the use of advanced modeling and/or simulation techniques, including Bayesian methods and predictive analytics, to optimize clinical trial designs and data analytics.
Applies innovative approaches to utilize various data sources to improve clinical study designs, enhance data insights and gain end-to-end efficiencies for agile data-driven decision-making.
Drives the development and implementation of novel study designs, including adaptive designs and Bayesian model-based designs, and advanced data analytic tools (R-Shiny apps/statistical software tools) using state-of-art statistical methodology in accordance with regulatory requirements.
Provides innovative statistical and methodological approaches to specialized complex challenges related to optimizing clinical trial designs, leverage artificial intelligence and machine learning, enhance predictive analytics and causal inference and advanced statistical methods to support real-world evidence and personalize medicine strategies.
Represents the Statistical Innovation group with respect to statistical/innovative aspects of clinical development programs and products to internal and external stakeholders.
Maintains an external network of professional societies through active conference participation, academic institutions/experts, KOLs, industry wide working groups and Health Authorities to be recognized at the forefront of statistical innovation and new industry trends in clinical trial design and excellence in data analytics.
Provides training to Statisticians, clinical project teams and internal stakeholders on advanced statistical methods and novel study designs for knowledge sharing, implementation and large-scale adoption.