Supervisor, Data Management
Position Summary:
The Supervisor, Data Management will oversee the development and implementation of data management strategies to ensure data integrity and accessibility, specific to central lab services and sample management. The role requires collaboration with cross-functional teams to optimize data processes and enhance data quality. The Supervisor will provide training and support to team members, fostering a culture of continuous improvement and innovation. The Supervisor will also be responsible for developing performance metrics and reporting on team progress. A background in data analytics or a related field is preferred, along with proven leadership, and experience with data specific to clinical trials or clinical research organizations.
Essential functions of the job include but are not limited to:
Data Operations
- Lead the day-to-day operations of data reconciliation processes, including data review, discrepancy identification, and resolution.
- Lead the day-to-day operations for uploading/editing/validating of all clinical trial kit data into supply chain system and biospecimen inventory system.
- Lead the day-to-day operations of mapping and uploading work performed from operational systems into financial systems for billing and revenue recognition.
- Assist the team in preparation of various scheduled & ad hoc reports on daily, weekly, monthly and quarterly basis from operational and financial reports.
- ETL responsibilities to endure data is reliably transformed and stored to support operational and financial needs.
- Collaborate with clinical study teams, data managers, and project managers to address data discrepancies and ensure timely resolution.
- Monitor and manage data discrepancies between operational systems (e.g., Smartsheet, biospecimen inventory system, and site data) and financial systems (e.g., ERP system)
- Identify and troubleshoot operational problems, issues, obstacles, and barriers for studies based on metrics data, audit reports, and input from project team members and other stakeholders.
Data Governance
- Oversee project data entry process including development of data entry guidelines, training, data entry quality and resourcing.
- Identify and implement process improvements by participating and providing input on initiatives to simplify and automate complex processes.
- Ensure adherence to Good Clinical Practices (GCP) and regulatory guidelines for data management.
- Responsible for creating, revising, appropriate versioning and maintaining data management documentation. Oversee completeness of data management documentation.
- Participate in the development and maintenance of Standard Operating Procedures (SOPs) and corresponding process documentation related to data management, database management.
Leadership
- Provide leadership for cross-functional and organization-wide initiatives, where applicable
- Ensures that all data management project team members have been sufficiently trained
- Foster a collaborative team environment to achieve project goals.
- Assign workload, set clear expectations, and provide feedback to team members.
- Establish strong communications with Data Operations team, functional leads, project managers and all other stakeholders.
- Provide input, assesses and manage timelines. Assess resource needs for assigned projects, as needed.
Qualifications:
Minimum Required:
- 5+ years’ experience
- 2+ years of leadership experience
- Able to handle a variety of clinical research tasks.
- Broad knowledge of drug, device and/or biologic development and effective data management practices
- Experience in utilizing various clinical database management systems
- Expertise in data quality processes and standards
- Proficiency in Microsoft Office: Word, Excel, PowerPoint, Outlook.
- Excellent organizational and communication skills
- Professional use of the English language; both written and oral.
Preferred:
- Experience in a clinical, scientific or healthcare discipline.
- Understanding of data privacy regulations and compliance standards (e.g., GDPR, HIPAA)
- Experience with Power BI, Power Query, and/or Power Automate is a plus
- Experience with LIMS and/or Biospecimen Inventory and Management Systems
- Experience with Smartsheet
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