Data Scientist - Technical Services & Manufacturing Sciences

Job Summary 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.

Role Overview The Data Scientist - TSMS is responsible for delivering advanced analytics, predictive modelling, and digital innovation to support manufacturing and development processes across pharmaceutical operations. This role enables data-driven decision-making, process optimization, and compliance by partnering with global teams, site SMEs, and IT/digital functions. The Data Scientist manages analytics solution delivery, supports digital transformation, and ensures alignment with regulatory and business objectives.

Key Responsibilities Build, validate, and maintain multivariate statistical models (e.g., PCA/PLS) for real-time process monitoring Lead development and deployment of predictive models and multivariate analytics for process monitoring, anomaly detection, and performance optimization Collaborate with cross-functional teams (manufacturing, R&D, quality, IT) to design and implement data-driven solutions Work with Information Technology teams at Lilly to deliver secure, scalable analytics products (dashboards, data products, model services) and manage project interdependencies Support integration and harmonization of data across PLM, MES, LIMS, ERP, and analytics platforms Ensure data quality, integrity, and compliance with GMP and regulatory standards Facilitate knowledge transfer, training, and adoption of analytics solutions across global teams Track and report analytics project progress, risks, and outcomes to leadership and stakeholders Partner with technical teams to resolve data gaps, inconsistencies, and support validation activities Leverage data visualization and reporting tools (Power BI, Tableau, Seeq) for actionable insights Identify and implement process improvements and automation opportunities for digital transformation Maintain documentation, best practices, and knowledge repositories for analytics solutions Monitor adoption KPIs, gather user feedback, and drive continuous improvement in analytics capabilities Required Skills and Experience Technical and Functional Skills:

Proficient in statistical modeling, machine learning, coding languages, and predictive analytics (Python, R, SIMCA, JMP) Experienced in data integration, data quality assurance, and digital solution delivery Skilled in data visualization and reporting (Power BI, Tableau, Smartsheet) Knowledgeable in GMP, data integrity, and regulatory compliance. Experience working in Pharmaceutical manufacturing, Research & Development or other similar scientific environments Strong problem-solving, analytical, and detail-oriented mindset Effective communicator with experience working in global, cross-functional teams Ability to communicate complex insights to both technical and non-technical stakeholders Change-oriented and proactive in driving digital transformation Practical problem-solver who can work independently and within cross-functional teams; skilled at stakeholder management and communication Familiarity with cloud analytics (Azure/AWS), data pipelines, and APIs; experience with NLP for unstructured manufacturing knowledge is a plus Education & Experience Master s or Ph.D. in Data Science, Statistics, Engineering, Life Sciences, or related field 5+ years of experience in data science, analytics, or digital deployment in pharmaceutical or life sciences industry Experience in pharmaceutical GMP operations and TSMS or process development; strong understanding of manufacturing unit operations and process monitoring concepts Additional Information 10 - 20% travel may be required Some off-shift work (night/weekend) may be required to support 24/7 operations across global supplier network

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