Clinical Trials - Clinical Data Associate

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

At Lilly, we serve an extraordinary purpose. For more than 140 years, we have worked tirelessly to discover medicines that make life better. These discoveries start in Lilly Research Laboratories, where our scientists work to create new medicines that will help solve our world’s greatest health challenges.

**Please note, this is a hybrid position 3 days onsite/2 days remote**

Purpose:

This role is responsible for trial level clinical data strategy including database structure, content and meaning, acquisition, storage, retrieval, interchange, delivery and representation. This requires an in depth understanding of data collection, data flow management, data quality, data technology, dataset delivery, archiving and data standards. This role will collaborate with key study partners to define, implement, and deliver clinical data management packages. This role is responsible for providing trial leadership and ownership for a particular trial, set of trials, or programs.

Primary Responsibilities:

Portfolio Strategy, Planning and Delivery

• Define Lilly business requirements for the study/program for vendors to deliver

• Ensure that data management timeline and results are delivered to scope, cost, and time objectives

• Perform project monitoring and quality oversight of sourcing providers for end-to-end data management activities – from study set up through trial execution through dataset delivery

• Ensure vendor performance for the program-level flow of data, including across niche vendors and niche data sources (pharmacokinetic, immunogenicity, biomarker)

• Drives data flow design through consultation, review, and approval of vendor work. Ensures the data flow design is aligned with the project hypothesis

• Approve key outputs and results (i.e. Data Quality Delivery Plan, Data lock Plan, Project Plan, database, and observed datasets)

• Define and approve data quality and submission outputs and results

Project Management

• Ensure that data acquisition, database design, and observed dataset requirements are reflective of specific protocol objectives

• Specifies the data collection tools and technology platforms for the trial/program

• Drive standards decisions, implementation and compliance for the study/program

• Help create scope scenarios and negotiate outcomes with study teams while taking into account the cost and value of scenarios

• Facilitate/assimilate integration of disparate data sources into datasets for decision making

• Use therapeutic knowledge and possess a deep understanding of the technology used to review data to ensure database deliverables are consistent and accurate

• Effectively apply knowledge of applicable internal, external and regulatory requirements/expectations (MQA, CSQ, MHRA, FDA, ICH, GCP, PhRMA, Privacy knowledge, etc.) to data deliverables

Communication

• Act as primary communication point for all data management activities related to a clinical study.

• Report out status of data management milestones and data quality.

• Partner with external data vendors: understand specifications to import multiple types of data, work with technical groups to ensure timely loads of external data sets into the sponsor's database.

• Demonstrate excellent written and verbal communication skills, including the ability to represent the Data and Analytics organization and influence stakeholders to drive data-driven decisions.

• Partner with cross-functional team members to ensure trial success through robust oversight/review.

Process Improvement

• Continually seek and implement means of improving processes to reduce cycle time and decrease work effort

• Represent data sciences’ processes in multi-functional initiatives.

• Actively engage in shared learning across the Data and Analytics organization.

• Work with partners to increase vendor/partner efficiencies

Minimum Qualification Requirements:

• Master’s degree in a scie