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

Purpose:

The demand for high quality health economic and outcomes research (HEOR), health services research (HSR) and real-world evidence (RWE) to support drug development, health technology assessment/access decisions, product differentiation, clinical decision making, and shape the health policy environment continues to increase.  The Lilly Value and Access Health Outcomes and Medical Engagement (LVA HOME) team is looking for talented, energetic, creative, diverse, influential, and collaborative team members to join our function and Team Lilly.

The ­­­RWE research scientist will provide scientific influence and advanced analytics expertise in the generation of real-world evidence for Lilly’s portfolio. This role will generate RWE insights by leveraging analytic, clinical, scientific, and technological expertise. The RWE research scientist will advance data/analytical platforms for optimal use and deliver innovative tools/methods to further advance analytic outputs. The scientist may have duties ranging from analysis of real-world data, execution of research analytics, execution of feasibility studies to guide value-based arrangement (VBA) concepts, and delivering innovative tools and improved practices to increase the efficiency/productivity of data analytics. 

Primary Responsibilities: This job description is intended to provide a general overview of the job requirements at the time it was prepared. The job requirements of any position may change over time and may include additional responsibilities not specifically described in the job description. Consult with your supervision regarding your actual job responsibilities and any related duties that may be required for the position.

Observational RWE/RWD Research Analysis

• Provide scientific and analytic input to study protocols
• Develop analytical plans and specifications for VBA analytics, rapid cycle analytics, and RWE studies, particularly using secondary data sources, such as healthcare claims data, electronic medical records data, etc.
• Provide expert input on the fit-for-purpose assessment of real world data (RWD) and the development of RWD platforms, including collaboration with key partners in Tech@Lilly and our RWD strategy team.
• Perform quality checks and peer-review of data and analytics, and support the feasibility analysis of data, including simple sample size estimation.
• Transform RWD sources to analysis ready data sets to enable rapid generation of RWE.
• Apply the spectrum of advanced analytical methods to RWD, conduct appropriate statistical analysis, deliver study results on time.
• Clearly interpret study results and influence the project team to deliver scientifically robust RWE.
• Attend and influence in external forums and conferences as needed in dealing with RWE analytics and clinical/health information, particularly as it relates to RWE.

Communication of Results, Insights and Dashboards

• Collaborate with team members to write reports, draft abstracts/posters/manuscripts, create data visualizations, and communicate study results.
• Assist with, or be responsible for, communicating study results via dashboards, final reports, manuscripts, or oral presentations in group settings, as well as for communicating one-on-one with key population-based decision makers (PBDMs) and internal leaders.

Healthcare Industry Knowledge and Pilot Work

• Understand disease states, competitive landscapes, and healthcare environment in order to enhance the level of PBDM focus and collaboration and be seen as a strong scientific contributor.
• Train yourself as and when needed to support diversification of work, including data linkage to Lilly data backbone, data science methods, machine learning and artificial intelligence.
• Support and participate in cross-functional coaching, mentoring, and training.

Basic Qualification Requirements:

• Advanced degree, PhD, in quantitative field with 3+ years of experience (e.g. statistics, epidemiology, public health, data science) or a Master's degree in analytics related field with 7+ years of experience in real world data and real-world evidence generation

Other Information/Additional Preferences:

• Proficient in use of data analytic tools and analytics languages and statistical software (e.g. R, Python, SAS).
• Prior experience with commonly used RWD sources (e.g., administrative medical and pharmacy claims, electronic health records).
• Familiarity with observational study principles and study designs evidenced by previous research experience.
• Demonstrated history of contribution to peer-reviewed publications.
• Prior data and analytics experience in pharma, managed care or similar healthcare industry.
• Expertise in foundational data archetypes of structured and unstructured RWD, including various types of RWD
• Understanding of medical and pharmacy coding (e.g. NDC, ICD, CPT, HCPCS).
• Technical expertise and application with working knowledge of experimental design and statistical analysis
• Proficient with data visualization software and dashboard creation.
• Expertise with external health data and information standards for the structure, processing, and delivery of health information. This includes the issues of information representation and interoperability between systems.
• Demonstrated ability to influence and collaborate within and across cross-functional teams primarily residing in US time zones.
• Self-management skills with a focus on results for timely and accurate completion of competing deliverables.
• The position is geographically flexible
• Location: US Remote