Senior Data Analyst & Clinical Data Manager

Exeltis; Madrid; Híbrido; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A global pharmaceutical company in Madrid is seeking a Senior Data Analyst & Clinical Data Manager to drive data management and analysis for clinical trials. The ideal candidate will have over 5 years of experience in the Pharma sector, strong knowledge of GCP guidelines, and skills in data visualization tools. This role offers both an onsite and hybrid work model, along with a competitive salary and opportunities for growth.

Servicios

Professional development opportunities

Competitive salary

Formación

• Must have +5 years of experience in similar positions in Pharma sector.
• Fluent English; knowledge of other languages is an asset.
• Strong understanding of GCP guidelines and relevant regulations.

Responsabilidades

• Drive development of reporting and visualization for decision-making.
• Oversee clinical trial data management.
• Analyze data to identify patterns for clinical trials.

Conocimientos

Data analysis

Communication skills

Problem-solving

Project management

Knowledge of clinical data standards

Educación

Bachelor’s Degree in Life Science or Health Informatics

Herramientas

Python

SQL

Data visualization software

Descripción del empleo

In few words

Position : Senior Data Analyst & Clinical Data Manager

Location : Madrid (onsite)

Experience : +5 years of experience in similar positions in Pharma sector with experience at international level.

Global Responsibility

The Senior Data Analyst & Clinical Data Manager is a hybrid role responsible for driving the development of reporting and visualization activities that enable data‑driven decision‑making across Exeltis’ portfolio of clinical studies, while leading and ensuring accountability in all data management activities related to clinical trial projects. This role is responsible for managing and overseeing all aspects of clinical trial data management, from study start‑up to final database lock, while also delivering new solutions that optimise data workflows, facilitating the interpretation of clinical data trends, and ensuring compliance with regulatory and industry quality standards.

Specific Responsibilities 📌

Data Analytics :

• Analyzing and interpreting data to identify patterns that help drive decision‑making in clinical trials.
• Implementing clinical data standardisation and developing new solutions to ensure optimal management and interpretation of the clinical data.
• Developing key performance indicators (KPIs) to evaluate clinical trial progress.
• Generating data visualisation strategies and dashboards through the use of data from various databases and sources.
• Collaborate cross‑departmentally to develop new machine learning and artificial intelligence tools related to clinical data.
• Ensuring that study team members from different functional areas understand and deliver components affecting data to ensure the successful execution of deliverables.

Clinical Data Management

For the clinical trials conducted internally (in‑house model) :

• Serves as a primary point of contact for data management deliverables. Understands, mediates and solves issues related to data management study deliverables and escalates as required to Study Team or Manager (as applicable).
• Establishes strong communication with Study Team, functional leads and other stakeholders.
• Provides data management operational input into the study design, protocol development, study planning, study documents including the study risk register.
• Leads all data management aspects of a clinical study, including study planning, start‑up activities, conduct and database lock.
• Ensures data management study deliverables are in compliance with applicable SOPs and regulatory guidelines.
• Creates or reviews study level timelines for data management deliverables and ensures they are met on time.
• Develops study‑specific electronic data capture (EDC) systems: electronic case report form (eCRF) specifications, edit checks specifications.
• Validates and tests clinical database during User Acceptance Testing.
• Creates key functional plans and specifications, tailored to the study needs (e.g. Data Management Plan, eCRF Completion Guidelines, Data Review Plan).
• Develops data transfer agreements and specifications with vendors providing external data (e.g. laboratory results).
• Develops or provides support to Study Team in the development of other external systems capturing clinical data, e.g. ePRO / eCOA, RTSM / IRT and ensures that any data transfer requirements between the systems are documented and tested appropriately.
• Conducts training for site users / monitors / other study team members on some of the clinical systems, e.g. EDC, RTSM, eCOA.
• Manages user accounts in clinical systems governed by data management (activates / de‑activates users in the database in response to requests e.g. from Project Manager or Trial Manager).
• Performs review / data cleaning activities such as, but not limited to, study team data reviews, edit check and manual queries review, coding, SAE reconciliation and non‑eCRF data reconciliation (e.g. lab data, eCOA / ePRO).
• Supports coding of medical terms in the clinical database, if required.
• Evaluates different options and uses careful judgment to choose the most efficient and effective way to resolve issues that arise during study lifetime.
• Generates data listings and reports needed for data review by the other Study Team members.
• Monitors study status (e.g. enrollment, eCRFs completion, query rates) on an ongoing basis and provides data status reports to the Study Team.
• Updates applicable databases, as a result of change order and protocol amendment(s).
• Prepares / reviews database for data freeze and / or lock and archives it with related documentation.
• Providing feedback on SDTM datasets to ensure data are collected and represented in a manner that supports regulatory requirements to comply with CDISC standards (CDASH, SDTM and ADaM).
• Review the final SDTM, define.xml, annotated CRF and Clinical Study Data Reviewer’s Guides for EMA, FDA and PMDA submissions.
• Ensures that data management documentation is complete and up-to-date in the electronic trial master file (eTMF).

For clinical trials where any of the above activities have been outsourced to an external service provider :

• Oversees / manages the vendor to ensure that timelines and deliverables meet Exeltis and protocol requirements.
• Ensures that their work is done in accordance with effective work orders and Exeltis SOPs (if applicable).
• Participates in and supports RFP process (review RFP documents, pricing, evaluates the needs).
• Performs quality controls according to applicable plans, e.g. Data Management Plan, Data Review Plan.
• Review the creation and final SDTM, define.xml, annotated CRF and Clinical Study Data Reviewer’s Guides for EMA, FDA and PMDA submissions.

Other :

• Develops SOPs or guidelines to ensure data management activities are in accordance with Good Clinical Practice (GCP) and any other applicable regulations or local requirements.
• Promotes the implementation of clinical data standards to increase consistency, efficiency & productivity (creation of eCRF standards, documents / plans templates etc).
• Provides input into activities associated with regulatory inspections / audits for assigned studies.
• Provides input into activities associated with selection, validation and use of software systems, devices and vendors.
• Mentors and trains junior data managers and data analyst; serves as Subject Matter Expert (SME).

🕵️Requirements and personal skills

• Education : Bachelor’s Degree (or its international equivalent) in Life Science or Health Informatics.
• Languages : Fluent English, knowledge of other languages will be an asset.
• Experience (years / area) : +5 years of experience in similar positions in Pharma sector with experience at international level.
• Specific Knowledge : Strong understanding of Good Clinical Practice (GCP) guidelines and other relevant regulations (e.g. FDA, ICH, EMA). Strong working knowledge of data management tools and software. Knowledge of programming languages (e.g. Python, SQL), relational database terminology, reporting tools and data visualisation software.
• Travels : Willingness to travel 20%
• Personal skills : Demonstrated experience in managing multiple priorities in a highly dynamic environment.