Post by ncwebcenter on Aug 17, 2009 14:47:07 GMT -5
Principal Statistician / Manager, Statistics
Requisition ID: 55077
Position: Full-Time Regular
Open date: Aug 13, 2009
Functional area: Scientific
Location: Raleigh/Durham, North Carolina
Grade level: D1-C5
Required degrees: Doctorate Degree
Basic qualifications:
* Ph.D. in Statistics with at least 5 years experience in clinical discovery or development.
Preferred qualifications:
* Ph.D. in Statistics with at least 8 years experience in clinical development or discovery, or statistical consulting. Strongly prefer substantial experience in clinical pharmacology and early drug development.
Details:
The incumbent will drive innovation into drug discovery and development through close interacts within a matrix team environment involving scientists from the HIV and HCV Discovery Performance Units; CPK/Modelling & Simulation; Computational Biology; Genetics; Clinical Operations; Medical Development Statistics; and Clinical Epidemiology.
Candidate qualifications include:
• Clinical pharmaceutical industry experience or consulting experience with a working expertise as well as a proven track record of the successful application of Bayesian-based methods used to inform decision making in support of drug candidate progression. Broad knowledge of drug development processes and strategies. Extensive experience with the design, analysis and reporting of clinical studies, as well as contributions to the overall clinical development plan. Experience with regulatory agencies is a plus.
• Experience teaching Bayesian-based methods at the undergraduate or graduate level is a plus.
• Working expertise will include planning, designing, interpreting, communicating, and reporting of clinical adaptive, especially Bayesian-based, trial results. Prior experience with pharmacokinetic and pharmacodynamic endpoints is required.
• .A proven track record of creating processes (e.g., clinical trial simulations) to explore the performance of alternative trial designs to boost the confidence of stakeholders in the success of innovative approaches.
• Knowledge of model-based methods to support translational pharmacology by coupling in silico, in vitro, and preclinical data with relevant clinical outcome or biomarkers is also preferred.
• Ability to ensure statistically sound approaches, analysis, reporting, and interpretation of studies to clinical pharmacology studies, consistent with GSK standards and regulatory requirements, sufficient to support successful product registration and commercialization.
• Ability to effectively communication to matrix team members, putting information into perspective and a broad context. Proactively facilitate communication among fellow staff members and across the Discovery Biometrics Department to take advantage of knowledge gained on individual projects to share best practices, innovative designs and methods, therapy area knowledge, and continual improvements in efficiency.
• Strong written and verbal communication skills. Proven influencing and assertiveness skills. Credibility in interactions in the drug discovery/development matrix. Demonstrated record of building and maintaining effective strategic working relationships. Strong business partner focus is essential.
• Experience with meta-analytical modelling, Monte Carlo/Markov Chain methods, and linear as well as nonlinear dose response modelling. The individual must possess experience using relevant modelling and simulation software (e.g., WinNonlin, NONMEM, S+, R, Matlab, Trial Simulator, Bugs, Berkeley-Madonna, SAS)
The ideal candidate will possess
• An analytical and inquisitive mind with a proven track record for problem solving.
• Well honed written and oral communication skills are essential.
• A proven ability to build effective and trusting relationships with the members of interdisciplinary matrix teams which is necessary for the implementation of adaptive, especially Bayesian-based, clinical study designs.
• A proven ability to build powerful networks within and outside the company and use these relationships to achieve support for the planning and implementation of innovative approaches
• A proven ability to set up processes and encouraging others to create multiple options, strategies or contingency plans, where pros and cons are compared prior to deciding on the way forward.
To apply, send your resume to info@ncwebcenter.com
Requisition ID: 55077
Position: Full-Time Regular
Open date: Aug 13, 2009
Functional area: Scientific
Location: Raleigh/Durham, North Carolina
Grade level: D1-C5
Required degrees: Doctorate Degree
Basic qualifications:
* Ph.D. in Statistics with at least 5 years experience in clinical discovery or development.
Preferred qualifications:
* Ph.D. in Statistics with at least 8 years experience in clinical development or discovery, or statistical consulting. Strongly prefer substantial experience in clinical pharmacology and early drug development.
Details:
The incumbent will drive innovation into drug discovery and development through close interacts within a matrix team environment involving scientists from the HIV and HCV Discovery Performance Units; CPK/Modelling & Simulation; Computational Biology; Genetics; Clinical Operations; Medical Development Statistics; and Clinical Epidemiology.
Candidate qualifications include:
• Clinical pharmaceutical industry experience or consulting experience with a working expertise as well as a proven track record of the successful application of Bayesian-based methods used to inform decision making in support of drug candidate progression. Broad knowledge of drug development processes and strategies. Extensive experience with the design, analysis and reporting of clinical studies, as well as contributions to the overall clinical development plan. Experience with regulatory agencies is a plus.
• Experience teaching Bayesian-based methods at the undergraduate or graduate level is a plus.
• Working expertise will include planning, designing, interpreting, communicating, and reporting of clinical adaptive, especially Bayesian-based, trial results. Prior experience with pharmacokinetic and pharmacodynamic endpoints is required.
• .A proven track record of creating processes (e.g., clinical trial simulations) to explore the performance of alternative trial designs to boost the confidence of stakeholders in the success of innovative approaches.
• Knowledge of model-based methods to support translational pharmacology by coupling in silico, in vitro, and preclinical data with relevant clinical outcome or biomarkers is also preferred.
• Ability to ensure statistically sound approaches, analysis, reporting, and interpretation of studies to clinical pharmacology studies, consistent with GSK standards and regulatory requirements, sufficient to support successful product registration and commercialization.
• Ability to effectively communication to matrix team members, putting information into perspective and a broad context. Proactively facilitate communication among fellow staff members and across the Discovery Biometrics Department to take advantage of knowledge gained on individual projects to share best practices, innovative designs and methods, therapy area knowledge, and continual improvements in efficiency.
• Strong written and verbal communication skills. Proven influencing and assertiveness skills. Credibility in interactions in the drug discovery/development matrix. Demonstrated record of building and maintaining effective strategic working relationships. Strong business partner focus is essential.
• Experience with meta-analytical modelling, Monte Carlo/Markov Chain methods, and linear as well as nonlinear dose response modelling. The individual must possess experience using relevant modelling and simulation software (e.g., WinNonlin, NONMEM, S+, R, Matlab, Trial Simulator, Bugs, Berkeley-Madonna, SAS)
The ideal candidate will possess
• An analytical and inquisitive mind with a proven track record for problem solving.
• Well honed written and oral communication skills are essential.
• A proven ability to build effective and trusting relationships with the members of interdisciplinary matrix teams which is necessary for the implementation of adaptive, especially Bayesian-based, clinical study designs.
• A proven ability to build powerful networks within and outside the company and use these relationships to achieve support for the planning and implementation of innovative approaches
• A proven ability to set up processes and encouraging others to create multiple options, strategies or contingency plans, where pros and cons are compared prior to deciding on the way forward.
To apply, send your resume to info@ncwebcenter.com