Required Qualifications & Skills:
- 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&D Analytics, Data Analysis, Business Analysis, or related roles.
- Proven experience working with Biopharma / Pharmaceutical / Life Sciences clients.
- Strong understanding of Clinical/R&D processes, systems, and data.
- Experience working with or analyzing data from systems such as CTMS, EDC, RIM/Regulatory systems, clinical planning systems, and other R&D platforms.
- Understanding of clinical product hierarchies, study/trial structures, site and subject data, milestones, and related R&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&D Domain Knowledge – strong understanding of clinical development, clinical operations, clinical trials, and R&D processes.
- Clinical/R&D Systems & 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&D data domains.
- SQL & Data Analysis – ability to independently query, analyze, validate, reconcile, and troubleshoot complex datasets.
- Data Quality & Validation – experience with data profiling, reconciliation, business-rule validation, issue investigation, and root-cause analysis.
- Data Mapping & Lineage – understanding of source-to-target mapping, data transformations, data definitions, and data lineage across systems.
- Requirements & Analytical Thinking – ability to translate Clinical/R&D business needs into data requirements, business rules, metrics, and analytical specifications.
- Stakeholder Management – ability to work effectively with Clinical/R&D SMEs, business stakeholders, data engineers, architects, and BI teams.
Key Skills:
- Gather, analyze, and translate Clinical/R&D business requirements into data requirements, business rules, metrics, and analytical specifications.
- Analyze clinical and R&D datasets to identify trends, anomalies, inconsistencies, and data- quality issues.
- Understand data across key Clinical/R&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&D KPIs, metrics, data definitions, and reporting logic.
- Collaborate with Data Engineers, Data Architects, BI Developers, and Clinical/R&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.
Skills:- Data Analytics, Business Analysis, SQL, Pharmaceutics and Life sciences
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