Senior Clinical Data Analyst

Responsibilities:

• Gather, analyse, and translate Clinical/R and D business requirements into data requirements, business rules, metrics, and analytical specifications.
• Analyse clinical and R and D datasets to identify trends, anomalies, inconsistencies, and data- quality issues.
• Understand data across key Clinical/R and D source systems, their relationships, data flows, and downstream analytical use.
• Perform data profiling, reconciliation, validation, source-to-target analysis, and root-cause analysis using SQL and other analytical tools.
• Define and validate clinical/R and D KPIs, metrics, data definitions, and reporting logic.
• Collaborate with Data Engineers, Data Architects, BI Developers, and Clinical/R and D stakeholders to deliver analytics solutions.
• Contribute to analytical datasets, semantic models, data products, and data lineage initiatives.
• Support UAT, test case development, defect investigation, and business sign-off.
• Facilitate workshops and stakeholder discussions to clarify requirements and resolve data-related issues.
• Maintain functional, data, and analytical documentation throughout the delivery lifecycle.
• Support data governance activities including data quality, Critical Data Elements (CDEs), metadata, and lineage.
• Support Agile delivery activities including backlog refinement, user stories, acceptance criteria, and sprint execution.

Requirements:

• Bachelor's or Master's degree in Life Sciences, Pharmacy, Biotechnology, Clinical Research, Statistics, Data Science, Computer Science, Engineering, Business or a related field.
• 5-8 years of experience in Clinical Data Analysis, Clinical/R and D Analytics, Data Analysis, Business Analysis, or related roles.
• Proven experience working with Biopharma / Pharmaceutical / Life Sciences clients.
• Strong understanding of Clinical/R and D processes, systems, and data.
• Experience working with or analysing data from systems such as CTMS, EDC, RIM/Regulatory systems, clinical planning systems, and other R and D platforms.
• Understanding of clinical product hierarchies, study/trial structures, site and subject data, milestones, and related R and D data domains.
• Strong SQL and data analysis capabilities.
• Experience with data quality, validation, reconciliation, data mapping, and root-cause analysis.
• Understanding of data warehousing, BI, reporting, data integration, and analytical data models.
• Strong communication, stakeholder management, documentation, and problem-solving skills.
• Experience working with cross-functional and geographically distributed teams.
• Familiarity with Agile/Scrum and tools such as Jira or Azure DevOps.

Must-Have Skills:

• Biopharma/Life Sciences Client Experience - proven experience working with Biopharma, Pharmaceutical, Biotechnology, Clinical Research, or Life Sciences clients.
• Clinical/R and D Domain Knowledge - strong understanding of clinical development, clinical operations, clinical trials, and R and D processes.
• Clinical/R and D Systems and Data - practical understanding of systems such as CTMS, EDC, RIM, eTMF, Study Startup, and clinical planning/portfolio management systems such as Planisware, along with the data generated and consumed across these systems.
• Clinical Data Structures - understanding of clinical product/asset hierarchies, study/trial structures, sites, subjects, milestones, and relationships between key R and D data domains.
• SQL and Data Analysis - ability to independently query, analyse, validate, reconcile, and troubleshoot complex datasets.
• Data Quality and Validation - experience with data profiling, reconciliation, business-rule validation, issue investigation, and root-cause analysis.
• Data Mapping and Lineage - understanding of source-to-target mapping, data transformations, data definitions, and data lineage across systems.
• Requirements and Analytical Thinking - ability to translate Clinical/R and D business needs into data requirements, business rules, metrics, and analytical specifications.
• Stakeholder Management - ability to work effectively with Clinical/R and D SMEs, business stakeholders, data engineers, architects, and BI teams.

Skills

CTMS, Clinical, Data Analysis, EDC, Lineage, Mapping, RIM, Reconciliation, SQL, Validation