Associate Director, Centralised Monitoring at Thermo Fisher Scientific

Job Description

We are vital links between an idea for a new medicine and the people who need it. We are the people of PPD clinical research services — thousands of employees in locations worldwide connected by tenacity and passion for our purpose: to improve health. You will be joining a truly collaborative and winning culture as we strive to bend the time and cost curve of delivering life-saving therapies to patients.    

PPD's Centralised Monitoring group delivers a new approach to risk surveillance and centralized statistical monitoring, combining the power of statistical and analytical tools with expertise from operationally experienced staff to monitor and manage clinical study data. Centralised monitoring staff explore study data holistically to pinpoint meaningful signals, resulting in more efficient and effective issue resolution and a proactive approach to risk detection. Using this data-driven approach, PPD can address study problems or site performance quickly, directing remediation activities where needed and positioning on-site monitoring activity in a targeted approach.

Data analytics is an integral part of PPD’s risk-based monitoring (RBM) strategy and supports centralized monitoring efforts. Ongoing data assessments from our data analytics group allows to adapt monitoring plans dynamically so that CRA's can focus on the factors that have the greatest impact on data integrity and subject safety. Regardless of the percentage of source data verification (SDV), our centralized statistical monitoring approach identifies risk signals that may be difficult to detect through traditional review methods, such as on-site monitoring.

We evaluate data within and across studies, sites, countries and regions. Our analytic approach provides insight into:

• Data errors, deviations
• Trends, outliers
• Unusual variation (or lack of variation)
• Potential data manipulation, fraud
• Other systematic errors or data integrity issues.

As an Associate Director (AD) Centralised Monitoring, you’ll lead a global team to develop and deliver advanced analytics and cross-functional analysis to project teams to identify and reduce sources of risk in ongoing projects.

Essential Functions:  

• Oversees execution of Data Analytics, Centralized Monitoring function and project level risk reporting.
• Plans and presents functional risk trends to functional departments.
• Drives development and implementation of standard analyses, analytic tools, risk indicators to support CMA function.
• Manages client relationships, represents DA function to clients.
• Serves as department representative to internal departments, initiative and special interest functional groups.
• Supports departmental growth by planning, implementing, overseeing administrative and organizational efforts (e.g. hiring, project finances, resourcing, etc.).
• Manages staff/ lower level management, which may include interviewing and selection, job description preparation, professional development, goal setting, performance management, coaching and mentoring, employee counseling, and separations. Approves courses of action on salary administration, hiring, corrective action, and terminations. Reviews and approves time records, expense reports, requests for leave, and overtime.

Education and Experience: 

• Previous experience that provides the knowledge, skills, and abilities to perform the job (comparable to 10+ years) or equivalent and relevant combination of education, training, & experience. 5+ years of management responsibility. 
• In some cases, an equivalency, consisting of a combination of appropriate education, training and/or directly related experience, will be considered enough for an individual to meet the requirements of the role.

Knowledge, Skills and Abilities: 

• Demonstrated industry and clinical-trial specific deep functional-specific knowledge
• Excellent coaching, mentoring and teaching skills; demonstrated expertise in leading and motivating teams
• Strong analytical skills with ability to extract meaning from data and apply to solve real-world problems
• Excellent judgment and decision-making skills
• Strong technical skills interacting with data handling, analysis and visualization tools
• Leadership level communication and presentation skills; ability to represent department to senior levels of management and cross-departmental forums