Advisor - Research Scientist - Advanced Real World Evidence Data Scientist & Analyst

📋 Description

• • Eli Lilly and Company is seeking a highly skilled and motivated Advisor - Research Scientist specializing in Advanced Real World Evidence (RWE) Data Science and Analytics to join their dynamic Value and Access Health Outcomes and Medical Engagement (LVA HOME) team.
• • This pivotal role is designed for an individual who is determined to make life better for people around the world by leveraging advanced analytical expertise to generate critical real-world evidence (RWE) that supports drug development, informs health technology assessments, drives product differentiation, guides clinical decision-making, and shapes the health policy landscape.
• • The RWE Research Scientist will be instrumental in providing scientific influence and cutting-edge analytical capabilities to enhance Lilly’s portfolio through the generation of robust RWE insights.
• • You will be responsible for advancing data and analytical platforms for optimal utilization, and for developing and implementing innovative tools and methodologies to elevate the quality and efficiency of analytical outputs.
• • Key responsibilities span the entire RWE lifecycle, from the analysis of diverse real-world data (RWD) sources and the execution of complex research analytics, to conducting feasibility studies that inform value-based arrangement (VBA) concepts.
• • Furthermore, you will play a crucial role in delivering innovative tools and refining best practices to boost the overall productivity and effectiveness of data analytics within the organization.
• • In the realm of Observational RWE/RWD Research Analysis, you will provide essential scientific and analytic input into the development of study protocols, ensuring methodological rigor and strategic alignment.
• • You will be tasked with developing detailed analytical plans and specifications for VBA analytics, rapid cycle analytics, and comprehensive RWE studies, with a particular emphasis on utilizing secondary data sources such as healthcare claims data and electronic medical records (EMRs).
• • A significant aspect of the role involves providing expert input on the fit-for-purpose assessment of RWD, collaborating closely with key partners in Tech@Lilly and the RWD strategy team to ensure data quality and suitability for research objectives.
• • You will perform meticulous quality checks and peer reviews of data and analytical outputs, and support feasibility analyses, including preliminary sample size estimations, to guide research planning.
• • A core function will be transforming raw RWD sources into analysis-ready datasets, thereby enabling the rapid generation of high-quality RWE.
• • You will apply a wide spectrum of advanced analytical methods to RWD, conduct statistically sound analyses, and ensure the timely delivery of study results.
• • A critical skill will be the ability to clearly interpret complex study results and effectively influence project teams to ensure the delivery of scientifically robust RWE that meets the highest standards.
• • You will also be expected to represent Lilly in external forums and conferences, sharing insights and contributing to the broader discourse on RWE analytics and clinical/health information.
• • In terms of Communication of Results, Insights and Dashboards, you will collaborate effectively with team members to produce comprehensive reports, draft compelling abstracts, posters, and manuscripts for publication.
• • You will be responsible for creating impactful data visualizations that clearly communicate study findings and assist in or lead the communication of study results through dashboards, final reports, and oral presentations.
• • This includes presenting findings in group settings and engaging in one-on-one discussions with key population-based decision-makers (PBDMs) and internal leaders to drive understanding and action.
• • Regarding Healthcare Industry Knowledge and Pilot Work, you will cultivate a deep understanding of disease states, competitive landscapes, and the broader healthcare environment to enhance PBDM focus and collaboration, establishing yourself as a strong scientific contributor.
• • Continuous learning is encouraged, and you will be expected to train yourself as needed to support the diversification of work, including areas such as data linkage to Lilly’s data backbone, advanced data science methods, machine learning, and artificial intelligence.
• • You will also support and actively participate in cross-functional coaching, mentoring, and training initiatives, fostering a culture of knowledge sharing and development within the team.
• • This role offers a unique opportunity to contribute to life-changing medicines by providing the evidence needed to understand their value and impact in the real world.