Senior Clinical Data Scientist

Job Description Summary

-Provide timely & professional ongoing Mgmt of Data Mgmt/Coding/CDDRA-Database Development/DAP deliverables and of clinical trial data with respect to cost, quality and timelines for all assigned trials within Clinical Data Mgmt. Ensure consistently high quality data available for analysis and reporting. Develop content and redefine training modules into engaging & interactive applications. Leverage technology to ensure process simplification and training delivery. Follows Good Clinical Practices (GCP), data-handling procedures and guidelines. Participates in the review of clinical research protocols, reports and statistical analysis plans. Drives participation and input within Data Operations (DO) in the delivery of quality data and programs, processes and documentation -Manage data Load, Transfer and conform of Clinical trial data to NCDS compliant standards. The position is a key contributor with Data Provisioning team in ensuring that pharmaceutical drug-development plans in Novartis Global Drug Development are executed efficiently with timely and high quality deliverables.

Job Description

Major accountabilities:

• •Provides DM leadership across assigned trial (s) and Acts as the Trial Data Manager where needed -Demonstrates a business understanding of the compound (s) profile to identify and assist in successful application of data Mgmt processes.
• •Provides feedback to assure well written protocols and amendments.
• •Recognize and resolve protocol issues that may impact database design, data validation and /or analysis/reporting and that do not make the best use of available standards -Performs DM activities for start up of a study, Data Handling plan , Data Review Plan and performing user acceptance testing (UAT) -Manage local lab set up for the Clinical Database as applicable -Leads process and training deliverables within platform or processes.
• •Accountable for all aspects of the Process and Training within remit to ensure full compliance to all applicable global regulatory requirements is maintained and business objectives are achieved.
• •Accountable for all quality related aspects -Centralizes and aligns DO for audits and inspections.
• •Manages and measures Quality -Coordinates exception requests, deviations and corrective /preventative action plans -Performs DM hands on activities during the course of the study Performs ongoing review of all data generated from the clinical study including Third party and local lab data as well as SAE reconciliation where applicable -Responsible and accountable to ensure consistency of assigned trials with program level standards across DM documentation -Has proven abiity to use the tools available to generate listings for data review and where necessary provides these to the study teams.
• •Generates the study status reports for use at Clinical trial team meetings.
• •Supports and assists Junior staff for assigned trials -Provides effective input into DM initiatives and innovations for quality, efficiency and continuous improvement in scientific and operational excellence -Leads /Coordinates synonym review activities and dictionary version upgrade activities at trial /Program level.
• •Serves as primary study lead ensuring timely and quality deliverables by establishing and maintaining strong working relationships with study teams, and functional lines.
• •Acts as a technical consultant as required.

Minimum Requirements

• •Ability to work under pressure demonstrating agility through effective and innovative team leadership
• •Excellent interpersonal skills and proven ability to operate effectively in a global environment. Ability to influence and communicate across functions and to external stakeholder
• •Proven ability to interrogate and view data though various programming/GUI techniques
• •Excellent problem-solving skills
• •Ideally 4 years’ experience in Drug Development with at least 3 years in Clinical Data Management
• •Excellent verbal and written skills

Skills Desired

Clinical Data Management, Data Governance, Data Integrity, Data Management, Data Quality, Data Science, Waterfall Model