Clinical Data Analyst
Job Type | Permanent Full Time |
Location | London |
Area | Central London, UK |
Sector | Clinical Research |
Salary | £0 per year |
Currency | gbp |
Start Date | ASAP |
Advertiser | remoteapi |
Job Ref | 1459 |
Job Views | 7 |
- Description
Coronado Research are delighted to be recruiting for Data Analysts to join our team.
Are you a logical and technically creative Clinical Data Analyst? We need someone to support our customers visibility of their data through configuration and interpretation of data outputs using various programming languages and clinical trial systems.
The Clinical Data Analyst will play a crucial role in the integrity, quality, and reliability of clinical trial data and supporting regulatory compliance across studies. The successful candidate will be proactive and conscientious in their work, with a customer focused mindset and a highly collaborative attitude, able to work closely with cross-functional teams to ensure effective data oversight and analytics-driven decision-making.
Key Responsibilities
- Data preparation: Identify data sources and structure, conducting mapping and integration activities to ensure data availability for downstream activities.
- Technical set-up: Perform technical configuration of study systems, reports and analysis to generate insights required to manage study oversight and monitor risks and trends.
- Anomaly detection: Identify anomalies within clinical trial data using advanced analytical techniques, be able to recognise the importance of those anomalies and explain those anomalies to a non-technical audience.
- Quality Control: Conduct quality control activities to ensure the integrity of outputs and support the development journey of others through effective communication and analysis of quality control findings.
- Requirements Analysis: Interpret requests and requirements from stakeholders into technical solutions that deliver high quality results.
- Study team support: Develop and maintain dashboards, reports, visualisations and analysis summarising key study insights to support clinical study teams.
- Stakeholder communication: Collaborate with internal and external stakeholders to communicate data-driven findings and recommendations.
- Documentation: Ensure that documentation required to demonstrate regulatory compliance are maintained accurately.
- Regulatory Compliance: Ensure adherence to Good Clinical Practice (GCP), ICH guidelines, and regulatory requirements (FDA, EMA).?
- Industry Best Practices: Stay up to date with emerging trends and best practices in clinical data analytics.?
Skills and Experience Required
- Bachelor's or higher degree in a scientific, technical, or data-driven discipline.
- Proven experience of working with clinical data.
- Experience with one or more programming languages (e.g. SAS, R, or Python) for data manipulation and analysis.
- Strong knowledge of Good Clinical Practice (GCP), ICH guidelines, and global clinical trial regulations.?
- Ability to diagnose data discrepancies, apply critical thinking, and generate actionable insights.
- Excellent logical, analytical and problem-solving skills with a creative and curious approach to help drive innovation.?
- A conscientious approach to accuracy to ensure data reliability and compliance.
- Good customer focus, able to prioritise the needs and satisfaction of our customers and address and resolve conflicts constructively, respectfully and with resilience.?
- Ability to work both independently and collaboratively in a fast-paced, cross-functional environment, and to hold yourself and others to account for appropriate ethical behaviour and inclusivity.
- Dependable and a commitment to maintaining high data quality standards through a conscientious approach.?
- Strong communication and interpersonal skills for effective collaboration across teams.??
This is an exciting opportunity for a data-driven professional to make a meaningful impact on clinical research and patient outcomes. If you have a passion for data analytics and clinical research, we encourage you to apply.
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- Data preparation: Identify data sources and structure, conducting mapping and integration activities to ensure data availability for downstream activities.