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Mindrift

Málaga

Remote

EUR 45,000 - 75,000

Full time

8 days ago

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Job summary

Mindrift is seeking a Clinical Monitoring Analyst (Cluepoints) to support and lead centralized monitoring initiatives on a sponsor-dedicated project. This remote role requires SAS programming experience and strong communication and organisational skills to coordinate with the client.

As CMA, you will contribute to the Centralized Monitoring process by setting up, programming and refreshing the CM platform according to the study CMP.

Qualifications

  • Experience with SAS programming is mandatory.
  • Role involves lead programmer responsibilities on Cluepoints with strong communication and organisation.
  • Willingness to work on sponsor dedicated project and directly with the client.

Responsibilities

  • Set up and program QTL, KRI, and Data Quality for the Centralized Monitoring platform.
  • Support the Centralized Monitoring Lead in developing CM strategy and CM elements.
  • Perform refreshes of the Centralized Monitoring platform per CMP.

Skills

SAS programming
Communication skills
Organisational skills

Job description

Clinical Monitoring Analyst (Cluepoints) - Remote

London, United Kingdom
Budapest, Hungary
Reading, Berkshire, United Kingdom
Bloemfontein, South Africa
Dublin, Ireland
Centurion, South Africa
Barcelona, Spain
Sofia, Bulgaria
Madrid, Spain
Full time
R
This unique role within IQVIA lends itself to a Lead programmer on Cluepoints called Centralized Monitoring Analyst (CMA) with strong communication and organisation skills. Having experience with SAS programming is necessary.
This role is part of a sponsor dedicated project where you will be working with the client directly to manage deliveries.
The CMA contributes to the execution of the Centralized Monitoring process by performing the setup, programming and refresh(es) of the Centralized Monitoring platform, according to the study-specific Centralized Monitoring Plan (CMP).
Main responsibilities include:

  • Supports the Centralized Monitoring Lead (CML) in the development of the fit-for purpose CM strategy by contributing to the identification of the relevant CM elements to be implemented for the study (Quality Tolerance Limits (QTL), Key Risk Indicators, data visualizations and Data Quality Assessments)
  • Setup/Program QTL, KRI and Data Quality
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