What are the responsibilities and job description for the Biospecimen Data Manager I position at Precision for Medicine?
Position Summary:
The Biospecimen Data Manager I (BiospecDM I), virtual Sample Inventory Management (vSIM), will support the execution of client projects for QuartzBio’s Sample Inventory Management (SIM) service line. This role will be responsible for generating mapping specifications of source data into a Master Sample Inventory (MSI) and generate reporting on the MSI
Essential functions of the job include but are not limited to:
- Create mapping specifications of source data (e.g. data from EDC, central lab, specialty labs) into an MSI
- Validate mapping specifications created by others
- Create and modify reports outlining data discrepancies, reconciliation issues, sample projections, and gaps in sample collections
- Participate in research and development activities as appropriate
- Contribute to the advancement of Precision’s technology-based services in virtual Sample Inventory Management Product
- Develop documentation and data specifications
- Continuously monitor and evaluate data integrity, accuracy and completeness
- Performs work on problems of moderate scope potentially requiring modification of source code
- Perform other duties as assigned
Qualifications:
Minimum Required:
- Minimum of 2 years of relevant clinical data management or biospecimen operations experience
- Bachelor’s Degree
Other Required:
- Ability to work independently with little to no instruction on routine work
- Exercises judgment within generally defined practices selecting an approach for obtaining solutions
- Excellent communication and interpersonal skills
- Team player contributing to a positive, collaborative working environment
- Must be able to read, write, speak fluently and comprehend the English language
- Extended work hours may be required to meet business demands
Preferred:
- Proficiency in R or other coding experience.
- Experience with EDC systems and/or sample inventory systems
- Ability to work efficiently under Unix/Linux environment
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