Lead the development of business requirements for data curation through collaboration with R&D business and data platform teams
Maintain strong connections with analytical groups and R&D Data Platform teams to ensure seamless data integration and usage
Deliver pre-packaged, curated datasets aligned to business requirements for analytics
Document data specification that describes the required processing steps to generate analysis-ready datasets
Integrate diverse datasets (e.g., clinical trials, real-world data, omics) into a unified format for consistent analysis
Ensure all datasets meet analysis-ready and privacy requirements by performing necessary data curation activities
Provide coaching and peer review to ensure that the team’s work reflects industry best practices for data curation activities
Ensure that datasets are processed to meet conditions mentioned in the approved data re-use request
Write clean, readable code
Ensure that deliverables are appropriately quality controlled, documented, and can be handed over to R&D Tech team for production pipeline implementation
Requirements
BSc/MSc/PhD (or equivalent) in Computer Science, Mathematics, Statistics, or related subject
Proven experience of handling various modalities of scientific clinical data such as clinical trial data (including biomarkers), real world data (RWD), omics etc.
Experience in Python, Databricks, Delta Lake, PySpark, Pandas, other data engineering frameworks
Proven ability to handle and process large structured, semi-structured, and unstructured datasets efficiently
Strong communication skills and expertise to translate business needs into technical data requirements and processes
Ability to quantify and provide insights to business impact and value creation from data curation activities
Experience with at least one of the industry data standards such as CDISC(ODM: CDASH, SDTM, ADaM), HL7 FHIR, OMOP(CDM) etc.
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