Senior Statistical Programmer
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 | 1483 |
Job Views | 5 |
- Description
Coronado Research are delighted to be looking for a Senior Statistical Programmer to support our customers. The Senior Statistical Programmer will play a crucial role in the growth of Coronado Research, working with our clients to deliver great results. 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 collection, manipulation, 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 collect data and generate insights required to manage study oversight and monitor risks and trends.
- Statistical insights: Use SAS to deliver statistical insights throughout clinical trials.
- 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 systems, dashboards, reports, visualizations and analysis ensuring 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 CDISC, 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 SAS and other programming languages (e.g. 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.
Please contact David Atkin for more information.
#SAS #statisticalprogramming
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- Data preparation: Identify data sources and structure, conducting mapping and integration activities to ensure data availability for downstream activities.