Director - Statistics (RWE)

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
Job Description
Job Description,
The Real-World Data (RWD) Project Statistician develops or assists in the development of study designs, protocols, and statistical analysis plans for non-interventional and real-world evidence (RWE) studies in collaboration with epidemiologists, physicians, HEOR and medical affairs scientists, data scientists, and other research colleagues. The Real-World Data (RWD) Project Statistician is responsible for working with data scientists to perform analysis from real-world data sources (e.g., claims, electronic health records, registries) and for analyzing data for RWE studies that address clinical, regulatory, and market access questions.
Primary Responsibilities: The job tasks listed below outline the scope of the position. The application of these tasks may vary, based upon current business needs.
Statistical Study Design and Analysis
Provide input on study protocol, design non-interventional studies (e.g., cohort, case-control, external/synthetic control arms, target trial emulation) and write protocols for the conduct of each study, aligned with regulatory and HTA guidance on RWE.
Be accountable for selecting statistical methods for data analysis of observational data (e.g., propensity score methods, inverse probability weighting, doubly robust estimators, G-methods, and sensitivity analyses for unmeasured confounding), authoring the corresponding sections of the protocol and the statistical analysis plan, and conducting the actual analysis once the analytic dataset is created.
Evaluate and select appropriate RWD sources (e.g., claims, EHR, registries, linked data) and assess their strengths and limitations for the research question.
Collaborate with data sciences in the planning and implementation of data quality assurance plans, including data fitness-for-purpose assessments, phenotype and algorithm validation, and evaluation of missingness and misclassification.
Maintain currency with respect to statistical methodology, maintain proficiency in applying new and varied methods, and to be competent in justifying methods selected.
Perform peer-review of work products from other statistical colleagues.
Influence team members regarding appropriate research methods
Communication of Results and Inferences
Collaborate with team members to write reports and communicate results.
Assist with, or be responsible for, communicating study results via regulatory submissions, HTA dossiers, manuscripts, or oral presentations in group settings, as well as for communicating one-on-one with key customers and presenting at scientific meetings.
Respond to regulatory and HTA queries on the validity and interpretation of RWE and interact with regulators, payers, and HTA bodies.
Therapeutic Area Knowledge
Understand disease states, real-world treatment patterns, competitive landscapes, the availability and limitations of RWD sources in the therapeutic area, and the regulatory and HTA environment for RWE in order to enhance the level of customer focus and collaboration and be seen as a strong scientific contributor.
Regulatory Compliance
Perform work in full compliance with assigned curriculum(s) and will be responsible for following applicable Corporate, Medical, local, and departmental policies, procedures, processes, and training, including data privacy and governance requirements for secondary use of patient-level data.
Statistical leadership and Teamwork
Introduce and apply innovative methodology and tools (e.g., causal machine learning, NLP on unstructured clinical notes, AI-enabled evidence generation) to solve critical problems.
Develop reusable analytic frameworks, code libraries, and standards that increase the speed, quality, and reproducibility of RWE generation.
Merge scientific thinking and business knowledge to identify issues, evaluate options and implement solutions.
Lead projects independently and work effectively across functions. Apply technical expertise to influence business decisions.
Minimum Qualification Requirements:
Ph.D. in Statistics, Biostatistics, Epidemiology, or a related quantitative field (e.g., Data Science, Computer Science) with at least 7 years of hands-on experience analyzing real-world data (e.g., claims, EHR, registries) and applying causal inference methods to answer comparative effectiveness or safety questions
Other Information/Additional Preferences:
Proficient in statistical programming languages/software such as SAS, R, Python, SQL, Spotfire, Stan, etc
Experience with large-scale data platforms and common data models (e.g., OMOP/OHDSI, Sentinel, Databricks, Spark).
Familiarity with good practices and reporting standards for observational research (e.g., ISPOR) and FDA/EMA/HTA guidance on RWE.
Publication record in pharmacoepidemiology, outcomes research, or RWE methodology.
Interpersonal communication skills for effective customer consultation
Teamwork and leadership skills
Technical expertise and application with working knowledge of experimental and observational design and statistical analysis
Self-management skills with a focus on results for timely and accurate completion of competing deliverables
Resource management skills
Creativity and innovation
Demonstrated problem solving ability and critical thinking
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).
Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is
$166,500 - $259,600
Full-time equivalent employ