Clinical Trials Data management/Statistical Programming Specialist

About this role

The European Medicines Agency (EMA) relies on the results of clinical studies conducted by medicines developers to inform its opinions on the authorisation of medicinal products. The clinical evidence is usually provided in the form of summary reports (clinical study reports) and in some cases complemented by line listings of individual patient-level clinical study data in pdf format. EMA and Heads of Medicines Agencies (HMA) recently started exploring the benefits of receiving, early in the evaluation of applications for marketing authorisations, individual patient-level data from clinical studies in electronic structured format. The aim is to deepen the regulators’ understanding in the evidence submitted to support these applications. Specifically, validation, characterisation and analyses of clinical study data are intended to help inform the assessment of efficacy and safety of new medicines, as well as pharmacokinetics (PK) and pharmacodynamics (PD), including modelling and simulation, and guide the selection of trial sites to verify compliance with Good Clinical Practice (GCP). 

To support this activity, EMA is looking for data management and statistical programming specialists experienced in the curation and management of clinical study data, and/or in the development of dynamic visualisation and analysis tools. To support this activity, EMA is looking for clinical trials data management/statistical programming specialists experienced in the curation and management of clinical study data, and/or in the development of dynamic visualisation and analysis tools. The role(s) defined in this procedure underpin the Network Data Steering Group’s (NDSG) objectives to strengthen data use and management in medicines regulation, in alignment with the European medicines agencies network strategy to leverage data and artificial intelligence in the regulation of human and veterinary medicines in the EU.  

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Use of clinical study data in medicine evaluation | European Medicines Agency (EMA)
Network Data Steering Group (NDSG) | European Medicines Agency (EMA)
The European medicines agencies network strategy 2028

In this job you will

As a specialist in Data Science, you will be involved in several data management, data science and related activities. The main activities include:

As a specialist in statistical programming for clinical trials, you will contribute to a wide range of activities, including data validation, data management, data analysis and other related tasks. Your key responsibilities will include: 

• Support business processes’ development for the receipt, validation, characterisation, analysis, and visualisation of clinical study data submitted to the Agency by medicines developers; 

• Support the use of data analysis programmes and tools by creating, validating, executing and generating code for clinical study data analyses to answer questions relevant to regulatory decision making; 

• Perform analyses of clinical study data to support evaluations of marketing authorisation applications and prepare analysis reports consisting of tables, listings and figures (TFLs); 

• Support validation of clinical study data submissions to ensure adherence to CDISC standards, particularly ADaM and SDTM models; 

• Manage the quality and robustness of data according to the Agency’s data governance framework; 

• Develop training on the use of clinical study data analysis programmes and tools, and support knowledge sharing activities across the EU medicines regulatory network; 

• Develop guidance on the submission, validation, characterisation, analysis and visualisation of clinical study data for medicine developers and regulatory assessors; 

• Provide data management and analytics input aiming to deliver and maintain IT solutions to support the receipt, validation, characterisation, analysis, and visualisation of clinical study data; 

• Collaborate and communicate on scientific and data aspects of the work performed and on the Agency’s position on scientific and medicinal product issues with internal and external stakeholders (Member States, academic institutions, pharmaceutical companies, European and international organisations and other relevant stakeholders), including preparation and delivery of presentations and publications; 

• Contribute to the planning, the organisation, the running and in summarising of scientific meetings and workshops; 

• Work in a multicultural environment with multidisciplinary teams. 

Link to the full role description of the Data Scientist Specialist outlining generic duties and responsibilities.

Apply if you meet these eligibility criteria:

General conditions:
1. enjoy full rights as a citizen of a European Union Member State, Iceland, Liechtenstein or Norway;
2. have a thorough knowledge of English (at least level C1) and a satisfactory knowledge of another official language of the European Union (at least level B2);
3. have fulfilled any obligations imposed by applicable laws concerning military service.

Specific conditions:
1. possess a university degree of a minimum of three years or more in Data Science, Informatics, Computer Science, Engineering, Statistics, Mathematics, Biology, Medicines, or Pharmacy or other fields of science that require advanced use of analytics skills, that must have been obtained by the closing date of this vacancy notice;
2. have at least 3 years of relevant professional experience after obtaining the relevant degree and before the closing date of this vacancy notice.

General Condition 1 and Specific Conditions will be verified firstly based on the application form and then you will be required to provide documentary evidence at the interview stage. Failure to present these documents may result in the disqualification from the selection procedure. Only eligible candidates will be assessed by the selection committee.

You will need

• General understanding of medicines development and design / execution of clinical trials 
• Competency in Data Management including understanding, manipulation, cleansing and validation of clinical study data as per CDISC standards; and/or 
• Competency in Data analytics, specifically in Statistical Programming including development, validation and maintenance of statistical programs for the analysis of clinical study data 

Proven experience in the following: 

• Programming using statistical software (R and/or SAS) and development of dynamic data visualisation tools (e.g.. via R Shiny); 
• Experience in preparing reports consisting of narratives, tables, listing and figures summarising clinical study data analyses; 
• Working with clinical trial structured datasets as per CDISC standards such as SDTM and ADaM models and accompanied metadata; 
• Exposure to basic biostatistics 

Competencies you need to have:

Sub-family competencies    
Data management  (please see specific expectations listed under “You 
will need section”)    Advanced
Data analytics   (please see specific expectations listed under “You 
will need section”)   Intermediate
Applied knowledge    Intermediate

Grade competencies
Adaptability and agility    Intermediate
Analysing and problem solving    Intermediate
Prioritising and organising    Intermediate

Core competencies    
Ethics and integrity    Intermediate
Team collaboration    Intermediate
Customer centricity    Intermediate
Results orientation    Intermediate
Communication    Intermediate
Cross-cultural sensitivity    Intermediate
Continuous learning and self-development    Intermediate

For more information about definitions of competencies and associated proficiency levels, please refer to the EMA Competency Framework.

These are considered as nice to have:

Education 

Completed PhD or master’s degree in one of the university degrees required for eligibility. 

Experience 

It will be of advantage if you have: 

• a track record in collaboration/publication on development or implementation of CDSIC standards  
• developed training and guidance materials; 
• worked in data analytics frameworks based on cloud technologies and/or AI technologies; 
• designed and written macros; 
• worked in a team and in a multicultural and multi-disciplinary environment; 
• worked with nonlinear mixed effects and/or mechanistic modelling software;  
• experience in model informed drug development (MIDD).