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.

Driving Innovation, Empowering Insights

• Understanding of clinical product hierarchies, study/trial structures, site and subject data,

milestones, and related R&D; data domains.

• Solid 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.

Only immediate joiners are considered.

Skills:- SQL, Pharmaceutics and Life sciences

📌 Clinical Data Analyst (Bengaluru)
🏢 Hyrhub
📍 Bengaluru