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We are searching for the best talent for Associate Director, Signal Detection Scientist located in High Wycombe, UK.

The objective of this position is to lead the implementation of the Signal Management Group aggregate surveillance strategies for proactive and systematic detection and evaluation of new safety signals and emerging trends from post-marketing safety data for complex pharmaceutical products (e.g., large innovative programs, new therapeutic areas, or complex business partner relationships). These activities include the development, evaluation, piloting, and use of novel, computer-assisted tools and methodologies for signal detection and analysis of internal company safety data, international regulatory safety databases, and other data sources, e.g., claims and electronic medical records.

This position develops and implements product-specific surveillance plans, performs post-marketing signal detection activities, including signal validation, and participates in communication of emerging signals in forums, such as the Product Team Meetings and Safety Management Team Meetings. This position will also participate in the development of strategies for signal evaluation, including providing guidance on data sources and methods of analysis. The position may also perform activities supporting signal evaluation, such as ad hoc data mining of FDA FAERS, WHO VigiBase, and EMA EudraVigilance databases. The role also supports exploration of new signal detection methodologies, tools, and data sources to further the science of safety surveillance.

Primary responsibilities:

• Identify and assess (validate) new safety signals and trends by conducting systematic reviews of aggregate data with a focus on spontaneous adverse event reports. This includes signal detection activities in safety platforms, including our Company signal detection system and routine and ad hoc data mining in Empirica Signal.
• Prepare reviews of topics and summary analysis reports of safety data, with minimal guidance.
• Provide recommendations for further signal evaluation.
• Work with key customers and business partners (Medical Safety Officers, Safety Scientists, and other Safety Physicians) in developing and implementing product-specific surveillance plans.
• Participate as member of the matrix teams to address product specific safety issues, assist in the development of signal evaluation strategies, and participate in signal evaluation.
• Communicate findings from routine and ad hoc signal detection and assessment activities.
• Assist in the development and implementation of programmatic surveillance of adverse event reports for potential safety and product quality issues.
• Assist in the evaluation of novel, computer-assisted tools, and methodologies for analysis of safety data, including piloting new data source and methodologies.

Qualifications:

Education:

• Bachelor’s Degree required

• Advanced Healthcare-related Degree (e.g., RN, BSN, PharmD) with 3+ years industry experience in drug safety or related area and 1+ year of clinical/patient-care experience highly preferred

Required:

• Understanding of global health authority regulations and guidance’s surrounding the processing, reporting and evaluation of adverse events
• Understanding in single case medical assessment, post-marketing aggregate adverse event data reviews, evaluations of drug safety issues, adverse event dictionaries, core labeling, and Periodic Safety Review preparation
• Ability to lead projects
• Skillful in presenting complex data in a concise and understandable scientific manner
• Ability to thrive in a global, matrix environment - able to handle high workload and critical issues.

• Up to 10% travel – Domestic & International

Preferred:

• Ability to manipulate data in platforms such as Excel and SAS JMP
• Familiarity with applied epidemiologic principles of case series evaluation and understanding of computer-assisted methodologies for safety data analysis
• Knowledge in public health surveillance and tools (relevant work experience or Masters Public Health or equivalent)
• Knowledge of statistics, or system analytics, information systems engineering, or machine learning