Senior Lead Data Manager

Altasciences•Overland Park, KS

5d•$65,660 - $87,548

About The Position

The Senior Lead Data Manager is responsible for all data management activities from study start-up through database lock and archiving and independently supporting the needs of the clinical study and programs of studies. In addition, the Senior Data Manager has an active role in continuous improvement and acts as a leader in the department as demonstrated by successful mentoring and consistent study delivery over time.

Requirements

Bachelor's Degree in programming, health-related sciences, or relevant field and 5-8 years of Data Management experience. Experience may be considered in lieu of education.
Excellent verbal and written communication skills.
Professional attitude and strong interpersonal skills.
Ability to work well with a multi-disciplinary team of professionals.
Client-focused approach to work.
Flexible attitude with respect to work assignments and new learning.
Ability to prioritize workload.
Superior attention to detail.
Understanding of clinical research and the relationship of Data Management in the clinical study process.
Proven history of continuous improvement.
Strong technical aptitude and ability to adapt to multiple data management platforms.
Strong knowledge of electronic data capture (EDC) clinical data management systems.
Good computer skills (Microsoft Word, Excel, and Power Point) and ability to understand and adapt to various information technology (IT) systems.
Fluency in English is an essential requirement for the position of Senior Lead Data Manager including, but not limited to, for the following reasons: The requirement to have study protocols, designs and clinical research documents written and documented in English as required by industry regulatory agencies. The employee communicates frequently with Altasciences employees across Canada and the United States. As such, English is the main language used to correspond between offices.

Responsibilities

Follow department and company standard operating procedures (SOPs), forms, templates and policies. Provide feedback and update these guidelines as needed.
Act as the primary Data Management contact for the client and project team, proactively managing sponsor and interdepartmental expectations.
Develop strong client relationships that are driven by consistent study delivery in terms of quality and timeliness.
Develop, review, and maintain all study Data Management documentation.
Coordinate with Database Developers to ensure effective database build and timely go-live to meet the needs of the project.
Ensure the clinical database adheres to Clinical Data Acquisition Standards Harmonization guidelines allowing for optimal SDTM dataset programming.
Suggest design for standard and non-standard data collection, identify any gaps in data collection, and challenge collection of unnecessary data.
Define electronic case report form (eCRF) and edit check specifications to support data collection and analysis required per protocol.
Take responsibility for and guide effective quality control (QC) review and user acceptance testing (UAT) of the clinical database prior to its release into production, including oversight of staff performing these tasks.
Delegate and collaborate with Data Managers on data management cleaning activities including listing review, issuing and closing queries, and external vendor data reconciliation per protocol, department and client standards, and International Conference on Harmonisation (ICH) Good Clinical Practice (GCP) guidelines within the timelines expected by the client and project team.
Ensure data are properly reviewed in accordance with the Data Management Plan (DMP) and department and sponsor guidelines and that cleaning is effective and timely.
Track eCRFs to ensure appropriate updates and that all missing or discrepant data are queried appropriately.
Monitor key study metrics and provide status reports to the sponsor and project team.
Maintain the Data Management documentation for the trial master file (TMF) according to department and Project Management processes.
Provide input on study timelines, identify risks, and communicate mitigation strategies to the Project Manager.
Provide input into improving the efficiency of data management tasks.
Lead and participate in intradepartmental or interdepartmental process and quality improvement initiatives.
Oversee direct reports as assigned.
Mentor and train other team members and/or develop training materials as needed.