Lundbeck is looking to advance patient journey analytics by developing data-driven insights to help uncover access barriers, identify drop-off points, and improve the patient journey. This role will help shape the foundation for scalable, insight-driven approaches to help improve access and engagement across the portfolio and contribute to building the data ecosystems and analytics frameworks needed to support both in-line and future products where understanding the patient journey is crucial.
Requirements
- Proficiency in SQL, Python, or R, including experience building datasets, performing statistical analysis, and developing analytical models.
- Proven track record of independently designing and executing analytics projects and delivering insights that drive responsible, strategic decisions.
- Strong analytical and problem-solving skills, with the ability to interpret complex data and translate it into actionable insights.
- Experience with patient access analytics, such as evaluating hub program performance, identifying access friction points, or assessing the impact of patient services on time to therapy.
- Experience working with data visualization tools such (e.g., Tableau, Power BI, etc.) to create dynamic and interpretable dashboards.
- Familiarity with compliant experimental design and measurement approaches (e.g., A/B testing, pre/post, matched cohort analysis).
- Working knowledge of healthcare compliance frameworks and privacy regulations, including HIPAA, CCPA, CDPA, and PhRMA Code.
Responsibilities
- Advance patient journey analytics through tokenization and linking of privacy-compliant, de-identified patient‑level data sources to create a unified longitudinal view.
- Perform hands-on analyses to identify and quantify patient drop-off and translate findings into evidence-based, unbiased insights that help improve patient access and support outcomes.
- Develop reporting and analytics to support omnichannel performance tracking, patient program optimization, and compliant field access engagement.
- Apply statistical and advanced analytic methods (e.g., regression, time-to-event, clustering, segmentation) to uncover patterns in patient behavior and support hypothesis-driven, non-promotional analytics.
- Support the design and interpretation of compliant A/B tests and experimentation, ensuring appropriate governance and analytic rigor.
- Develop frameworks and scalable methodologies to monitor patient flow and engagement program effectiveness over time.
- Collaborate cross-functionally with data strategy and IT to design and implement secure, auditable patient journey data frameworks in alignment with HIPAA, CCPA, CDPA, and other relevant U.S. privacy regulations.
Other
- Remote opportunity - Open to candidates anywhere in the greater United States
- 6+ years of experience in data science, statistics, analytics, or a related field, with a focus on patient/customer analytics with 3+ years of experience working with patient-level healthcare industry data (e.g., IQVIA, Symphony or Komodo claims data, specialty pharmacy status data, EHR data, hub/copay program data, etc.).
- Strong understanding of U.S. healthcare system dynamics, including payer reimbursement pathways, specialty distribution models, and the design and operational flow of patient services programs such as hub, copay, and PAP.
- Strong communication and data storytelling skills, with the ability to explain complex findings to both technical and non-technical stakeholders.
- Ability to manage competing priorities and work collaboratively in a fast-paced environment with strong attention to detail and execution.
