Clinical Data Manager
vor 1 Woche
- CRF design
- Database design and set-up
- Creation of Data Management Plan and Data Validation Plan
- User acceptance testing
- eCRF completion guideline
- Data cleaning, SAE reconciliation, query management
- Medical coding (e.g., MedDRA, WHO-DD)
- Programming of plausibility checks
- Creation of SDTMs, and cSDRG is an advantage
- University degree in data science, statistics, computer science, or comparable studies
- At least two years of professional experience as a data manager with responsibility for clinical studies
- Knowledge of CDISC standards (SDTM, , cSDRG)
- Knowledge of relevant terminology in clinical and non-clinical research
- Knowledge of relevant guidelines GCP, ICH
- Quick comprehension and analytical thinking
- Team player with high degree of initiative
- Good English skills, German is an advantage
We value communication, flat hierarchies, open corporate culture, and a harmonious work environment. We offer comprehensive individual development opportunities, continuous trainings, and flexible working hours. A modern and bright office with a subsidised canteen, as well as the opportunity to work 2 days per week from home are part of our everyday working life. Full remote work from anywhere in Germany for those who do not live in Munich can be discussed. You will join an interdisciplinary team allowing you to discuss with and learn from peers with many different backgrounds.
Question?If you have any questions, please feel free to contact us by e-mail
About usStaburo GmbH is a data science company, specialized in statistical consulting, programming and bioinformatics for healthcare projects. Our core competencies include Clinical Statistics, Translational Medicine & Biomarkers, Phase I & Pharmacokinetics/-Dynamics, Data Transparency & Disclosure Services, Health Technology Assessment and Bioinformatics. Our customers are international pharmaceutical companies, CROs, biotech companies and medical device manufacturers. Our steadily growing team supports our clients efficiently from study design to data analysis and finally the disclosing and posting of trial results.
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