• Serves as Functional Lead for Clinical Data Science on complex project with diverse scope, including primary contact for internal liaison between Clinical Data Science and Project Management, Clinical Monitoring, and other functional groups.

• Acts as central steward of clinical data quality, monitors risks through the holistic review of clinical and operational data, using detailed knowledge of the protocol, taking into account the specific therapeutic area aspects of the protocol related to the data collected and aligning with cross functional operational plans to drive comprehensive clinical data quality

• Ensures the required data elements and corresponding data quality oversight steps are identified to support the defined study analysis

• Works with assigned project teams to communicate, address, troubleshoot and resolve complex data related questions and recommends potential solutions; escalates issues which potentially impact patient safety and study analysis

• Coordinates cross functional data cleaning activities to ensure quality standards and timelines are met for clinical data deliverables

• Develops the clinical data acquisition plan and corresponding data flow diagram for complex studies, assess risks associated with protocol design or program level strategies, study set parameters that could impact the credibility and reliability of the trial results within a program of studies. Aligns data flow with the study protocol to ensure data collected meets regulatory and study endpoint requirements.

• Design and drives the development of analytical tools, utilizes analytical platform/dashboard to detect potentially unreliable data that may impact the validity of the trial results.

• Demonstrates understanding of advanced technology method and the scope of applicability for study or program of studies

• Performs analytic reviews as defined in scope of work and data acquisition plan, identifies root cause to systematically resolve complex data issues

• Monitors and communicates project progress to the Sponsor and project team including use of project status reports and tracking tools/metrics

• Ensures launch, delivery and completion of all Clinical Data Sciences activities and milestones according to contractual agreement and relevant Standard Operating Procedures (SOPs), guidelines, and regulations

• Perform metric collection and data analysis to support continuous process improvement

• Review, maintain budget and identify out of scope for Clinical Sciences activities, raise to PM to be implemented in required change order

• Plans, manages, and requests Clinical Data Science resources for assigned projects

• Coordinates the work of the assigned Clinical Data Science team

• Develops and maintains project plans, specifications, and documentation in line with SOP requirements

• Maintains documentation on an ongoing basis and ensures that all TMF filing is up to date for necessary files

• Participates in, and presents at internal, Sponsor, third-party, and investigator meetings on behalf of clinical data science responsibilities

• BA/BS in the biological sciences, computer sciences, mathematics, or data sciences and/or related disciplines in the natural science/health care space. MS degree is preferred. In lieu of degree, equivalent relevant work experience

• Clinical Data Science experience or an equivalent combination of education and experience

• Experience in Clinical Data Science practices and relational database management software systems

• In-depth knowledge of the drug development process and its impact on data quality, in particular risk-based approach, biometrics procedures, workflows.

• Sound knowledge of analytic modeling methods such as regression, classification and clustering

• Strong project management skills and knowledge of project management methodologies

• Strong analytical skills and knowledge of Artificial intelligence /machine learning methodologies preferred

• Demonstrated staff leadership skills

• Knowledge of ALCOA++ data quality principles

• Expertise in protocol interpretation, data collection and data cleaning specification development

• Experienced with data analysis/data review and visualization tool sets including but not limited to Python, R, Spotfire, SAS

• Knowledge of medical terminology, clinical data, and ICH/GCP regulatory requirements for clinical studies, in particular requirements applicable to Clinical Data Sciences

• Proficiency in MS Windows navigation, Word, Excel, PowerPoint, and email applications

• Effective oral and written communication and presentation skills

• Good organizational, planning, and time management skills with the ability to multitask under tight deadlines while providing attention to detail

• Ability to be flexible and adapt to change, to work independently, as well as part of a multi-disciplinary team

• Ability to make effective decisions and manage multiple priorities in a highly dynamic environment