Data Scientist – Drug Delivery Device Development

Eli Lilly and Company • Indianapolis, IN

1d • Onsite

About The Position

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. Organization and Position Overview: Delivery, Devices, and Connected Solutions (DDCS) sits within Eli Lilly's Product Research & Development organization. We are a diverse team of scientists and engineers responsible for discovering, designing, and developing patient-centric drug delivery solutions across a broad range of modalities — from injection devices to novel routes of administration and nanomedicines. DDCS drives the drug delivery innovation agenda across early and late development to meet the needs of an expanding portfolio that spans small molecules, biologics, and nucleic acid therapeutics. DDCS is organized around a matrix model with strong disciplinary and functional horizontals supporting innovation and commercialization verticals. Our vision is to get our medicines to more patients faster by accelerating reach and scale, guided by three strategic pillars: Delivery Systems, Robust & Sustainable, and Patient Experience + Outcomes. The Data Science horizontal within DDCS generates actionable scientific and business insights that accelerate innovation and de-risk commercialization across the DDCS matrix. Data scientists operate at the intersection of device engineering, drug delivery science, clinical evidence, and AI—partnering with AI application engineers, scientific ML specialists, and data engineers to build end-to-end analytical capabilities that directly shape product design decisions, device performance optimization, and patient outcome strategies. We are seeking an exceptional Data Scientist to join DDCS's data science team. This role leverages internal and external data to generate actionable scientific and business insights that drive innovation in drug delivery technologies. The ideal candidate combines deep analytical expertise with strong business acumen to identify high-value use cases, develop data-driven solutions, and communicate compelling data stories to senior leadership. You will play a pivotal role in influencing product design decisions, optimizing device performance, and advancing DDCS's mission to improve patient outcomes through innovative drug delivery systems—operating as a key horizontal contributor within the DDCS matrix.

Requirements

• PhD in Statistics, Biostatistics, Data Science, Computer Science, Computational Biology, Engineering, Physics, Applied Mathematics, or a related quantitative field
• Experience conducting independent research and developing novel analytical approaches, with demonstrated research excellence through publications, dissertations, or equivalent scholarly work,.
• Proficiency in Python, R, and/or ML frameworks (i.e. PyTorch, TensorFlow, scikit-learn) and visualization tools (i.e. Tableau, Power BI).
• Cross-functional collaboration and influence within a matrixed model
• Regulatory awareness and compliance mindset in GxP/GMP environments

Nice To Haves

• Post-PhD experience in pharmaceutical, biotechnology, medical device, or healthcare industries.
• Strong foundation in statistical analysis, machine learning, deep learning, and data manipulation through doctoral research or professional experience.
• Proven ability to work with complex, multi-dimensional datasets and translate analytical findings into actionable recommendations.
• Understanding of drug delivery mechanisms, pharmacokinetics, and device engineering principles.
• Experience with clinical trial design, analysis, and interpretation (adaptive designs, survival analysis, patient-reported outcomes).
• Analytical depth: statistical modeling, machine learning, and advanced data analysis
• Scientific curiosity and ability to formulate rigorous analytical questions from complex device/drug delivery problems
• Exceptional data storytelling: translating complex findings into executive-ready insights
• Strategic business acumen: connecting analytical work to portfolio and program decisions
• Mentorship and knowledge-sharing orientation

Responsibilities

• Use Case Identification & Solution Development Partner with engineers, scientists, and business stakeholders across innovation and commercialization verticals to understand needs and opportunities across the product lifecycle.
• Identify and prioritize high-impact use cases for data-driven solutions in formulation optimization, device design, quality assurance, and patient adherence.
• Design and implement analytical frameworks and predictive models to address specific business questions and technical challenges.
• Develop statistical models, machine learning algorithms, and simulation tools to support decision-making in research, development, and commercialization.
• Scientific & Business Insights Generation Analyze complex datasets from laboratory experiments, clinical studies, manufacturing processes, device sensors, and real-world evidence to extract meaningful scientific and business insights.
• Investigate device performance characteristics, patient usage patterns, drug stability, and delivery accuracy to identify opportunities for product improvement and innovation.
• Conduct exploratory data analysis to uncover trends, patterns, and anomalies that inform research priorities and strategic decisions.
• Synthesize findings from multiple data sources to provide holistic perspectives on device efficacy, safety, and market performance.
• Predictive Modeling & Advanced Analytics Build, validate, and deploy predictive models for device performance forecasting, failure mode prediction, patient outcome estimation, and quality control optimization.
• Apply statistical methods including regression analysis, hypothesis testing, survival analysis, and Bayesian inference to experimental and observational data.
• Collaborate with AI application engineers and scientific ML specialists to develop advanced models including deep learning, NLP, and computer vision applications.
• Implement model monitoring and performance tracking to ensure continued accuracy and reliability in production.
• Data Storytelling & Leadership Communication Translate complex analytical findings into clear, compelling narratives that resonate with both technical and non-technical audiences.
• Create executive-ready visualizations, dashboards, and presentations that communicate insights and recommendations to senior leadership.
• Present data-driven recommendations to influence product design, development strategies, and investment decisions across the DDCS matrix.
• Develop business cases with quantitative evidence to support new initiatives, process improvements, and strategic pivots.
• Cross-Functional Collaboration Work closely with data engineers to define data requirements, ensure data quality, and access appropriate data infrastructure.
• Collaborate with AI application engineers to transition models from research to production environments.
• Partner with clinical, regulatory, and quality teams to ensure analytical approaches align with compliance requirements and industry standards.
• Support research scientists and engineers by providing statistical consultation and analytical expertise.
• Data Strategy, Innovation & Mentorship Stay current with emerging analytical techniques, machine learning methods, and industry trends in medical device development and digital health.
• Identify opportunities to apply novel analytical approaches to solve longstanding challenges in drug delivery device development.
• Contribute to best practices, methodologies, and capabilities within the DDCS data science horizontal.
• Mentor junior team members and promote a culture of data-driven decision-making across the DDCS matrix.

Benefits

• Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance).
• In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree