Rocgjp00025742 Genetics And Genomics Data Manager

m/w/d, Basel-Stadt

The team needs data management support for the following:
Ingesting high dimensional (-omics) data by FAIR principles
Performing data reconciliation and data conformance checks
Providing solutions that allow an overview of data we have and linkage to patients/samples
The candidate will work closely with colleagues in Data Excellence to align on strategies and solutions.

The ideal candidate is someone who has experience of having worked with genetic/genomics next generation sequencing (NGS) data such as whole exome, whole genome and/or RNA sequencing data. An understanding of the end-to-end flow- Patient- Sample- Assay- data is preferred. Working with global CROS / vendors / central labs is preferred.

Tasks & Responsibilities:

• Support ingestion of High dimensional Genomic and Genetic data on studies
• Work with scientists, CROs/Vendors to pre-align on data transfer requirements (e.g. Metadata requirements)
• Manually create or provide fit-for-purpose tools that allow an overview of what patients, samples we have data for in our repositories and thereby facilitating high dimensional data reconciliation possible at a patient or sample level
• Perform data reconciliation checks on samples and data

Must Haves:

• MSc, PhD or similar qualification in a data science discipline combined with a degree or significant research experience in biology (e.g., statistics/ biostatistics, epidemiology, bioinformatics, health economics, computational biology, computer science, mathematics, outcomes research, public health, biology, medicine, psychology)
• 3 + years of relevant industry experience or a role as a project manager in a multi-lab/research group academic collaboration involving significant data generation and data analysis components
• Project Management, Ability to work in matrix teams, strong communications, influencing, negotiation, and networking skills
• Data Management experience with genetic and genomic data or bioinformatics analysis experience

Nice to Have:

• Understanding of the pharmaceutical industry
• Working with global CROs and vendors for data ingestion and acquisition
• Understanding of end-to-end flow- Patient-Sample-Assay-data in clinical trials
• Experience with LIMS systems, Sample management systems and data management tools

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