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Data Scientist – Technical Services & Manufacturing Sciences

Eli Lilly

Data Scientist – Technical Services & Manufacturing Sciences

full-timePosted: Aug 31, 2026Updated: Sep 1, 2026Hyderabad, India

Job Description

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. Data Scientist – Technical Services & Manufacturing Sciences (TSMS)Company OverviewLilly, a leading innovation-driven corporation is developing a growing portfolio of pharmaceutical products by applying the latest research from its own worldwide laboratories and from collaborations with eminent scientific organizations. Headquartered in Indianapolis, Indiana, Lilly makes life better – through medicines and information – for some of the world’s most urgent medical needs. Founded over 145 years ago, the company has sustained a culture that values excellence, integrity and respect for people. This has resulted in Lilly frequently being ranked as one of the best companies in the world at which to work. Lilly knows its business has prospered because of its employees – people with a talent for innovation and a passion for making a difference by finding treatments for the most stubborn diseases; people whose talent is matched by their generosity, and people with strong values and a determination to prevail, regardless of the challenges. Join our team – and make a difference in improving health for people all over the world!Manufacturing and Quality Technical Hub HyderabadLilly has made a strategic investment of more than $1B dollars to establish a Manufacturing and Quality technical hub. This hub will oversee the significant investment in contract manufacturing of starting materials and intermediates for API manufacturing in India and the technical services responsible for managing the scientific agenda for manufacturing and quality. The hub will be recruiting top talent in the areas of process engineering, chemistry, analytical and data sciences to build a cutting-edge scientific organization supporting the exciting manufacturing portfolio of Lilly.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 monitoringLead development and deployment of predictive models and multivariate analytics for process monitoring, anomaly detection, and performance optimizationCollaborate with cross-functional teams (manufacturing, R&D, quality, IT) to design and implement data-driven solutionsWork with Information Technology teams at Lilly to deliver secure, scalable analytics products (dashboards, data products, model services) and manage project interdependenciesSupport integration and harmonization of data across PLM, MES, LIMS, ERP, and analytics platformsEnsure data quality, integrity, and compliance with GMP and regulatory standardsFacilitate knowledge transfer, training, and adoption of analytics solutions across global teamsTrack and report analytics project progress, risks, and outcomes to leadership and stakeholdersPartner with technical teams to resolve data gaps, inconsistencies, and support validation activitiesLeverage data visualization and reporting tools (Power BI, Tableau, Seeq) for actionable insightsIdentify and implement process improvements and automation opportunities for digital transformationMaintain documentation, best practices, and knowledge repositories for analytics solutionsMonitor adoption KPIs, gather user feedback, and drive continuous improvement in analytics capabilitiesRequired Skills and ExperienceTechnical 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 deliverySkilled 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 environmentsStrong problem-solving, analytical, and detail-oriented mindsetEffective communicator with experience working in global, cross-functional teamsAbility to communicate complex insights to both technical and non-technical stakeholdersChange-oriented and proactive in driving digital transformationPractical problem-solver who can work independently and within cross-functional teams; skilled at stakeholder management and communicationFamiliarity with cloud analytics (Azure/AWS), data pipelines, and APIs; experience with NLP for unstructured manufacturing knowledge is a plusEducation & Experience:Master’s or Ph.D. in Data Science, Statistics, Engineering, Life Sciences, or related field5+ years of experience in data science, analytics, or digital deployment in pharmaceutical or life sciences industryExperience in pharmaceutical GMP operations and TSMS or process development; strong understanding of manufacturing unit operations and process monitoring conceptsAdditional Information:10 – 20% travel may be requiredSome off-shift work (night/weekend) may be required to support 24/7 operations across global supplier networkLilly 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 does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.#WeAreLilly

Locations

  • Hyderabad, India

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

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