Clinical Data Strategist

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.

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location.  The anticipated wage for this position is

$76,500 - $162,800

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.

Purpose:

The Clinical Data Strategist is a cross functional Data and Analytics scientific leader and key partner with other Data and Analytics Leaders and cross functional staff. Clinical Data Strategist is accountable for setting end to end clinical data strategy, driving cross functional alignment, and realizing improvements in drug development data solutions, technologies, systems, data processes, data products and/or services for a Business Unit and Therapeutic Area. The scope of the Clinical Data Strategist role includes elements of clinical research from early clinical development to post launch clinical research and regulatory submission/inspection activities.

Primary Responsibilities:

Portfolio Delivery

• Partner with internal and external teams to provide proactive strategic, scientific and technical input for clinical data planning and execution that enable efficient delivery of data

• Accountable for driving project decisions related to clinical data execution options, including integrated functional sourcing, innovation, technology, automation, AI/ML solutions, analytics and data collection modality

• Ensure strong linkages exist between clinical design, execution, analytics, delivery and submission

• Ensure data from different sources are consistent and easily consumable

• Map collected data into predictable source/raw data

• Optimization of study build and study build automation tools

• Electronic and/or data capture (eDC, eCOA)

• DDC (Direct Data Capture)/eSource

• Integration of new data capture processes and EHR/EMR-EDC integration

• DHT (Digital Health Technology)

• Data transfer enhancements

• Image tracking and reconciliation

• Dashboards (CTMS, Site Enrollment Readiness, Insights)

• Early detection of potential issues with Clinical Trial Data

• Collaborate with Clinical Data Associate and other Data and Analytics staff on data collection design and optimization

• Ensure critical data and processes are implemented and optimized

• Understand inconsistencies in data and provide feedback to standards team

• Support submission, inspection and regulatory response activities

Enterprise Leadership

• Exhibit strong business acumen, strong problem-solving skills and agility to adjust to changing business priorities and needs.

• Represent the Data and Analytics organization at appropriate internal and external venues.

• Accountable for fiscal responsibility of execution of clinical data plans

• Ensure that activities are performed according to established guidelines, best practices, and in compliance with all laws and regulations.

• Drive shared learning and end to end process expertise, demonstrating continuous improvement on key metrics.

• Proactively define and drive data strategies to accelerate data execution, delivery, integration, and submission.

• Bring greater value to the portfolio by anticipating issues and identifying opportunities for which data solutions can be applied regardless of source.

• Articulate the value of data solutions in terms of reliability, time, cost, quality, and scalability.

• Integrates cross-functional and/or external information and applies technical knowledge to data-driven decision making.

• Anticipate and resolve key technical, operational, or business problems that impact the Data and Analytics organization.

• Interacts with regulators, business partners and outside stakeholders on business issues.

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