PHARMAFull-time
Data Scientist – Technical Services & Manufacturing Sciences
By Admin · Manufacturing, Production & Supply Chain
HYDERABAD (IN)ONSITEPOSTED: 9/10/2026
PHARMAFull-time
HIRING ORGANIZATIONELI LILLY AND COMPANYPharmaceuticals and Biotechnology
ROLE OVERVIEW
Drive advanced analytics, predictive modeling, and digital innovation across pharmaceutical manufacturing and development. The role combines data science with GMP-regulated operations to improve process monitoring, optimization, quality, and data-driven decision-making.
ROLE DEFINITION & RESPONSIBILITIES
- •Build, validate, and maintain multivariate statistical models such as PCA and PLS for real-time process monitoring
- •Develop and deploy predictive models for process monitoring, anomaly detection, and performance optimization
- •Partner with manufacturing, R&D, quality, IT, and global technical teams to implement data-driven solutions
- •Deliver secure and scalable analytics products including dashboards, data products, and model services
- •Integrate and harmonize data across PLM, MES, LIMS, ERP, and analytics platforms
- •Ensure data quality, integrity, GMP compliance, and support validation activities
- •Use Power BI, Tableau, Seeq and related tools to generate actionable insights and drive automation
- •Track project outcomes, support training and adoption, maintain documentation, and drive continuous improvement
Reporting Hierarchy: Reports to the appropriate TSMS/Manufacturing and Quality technical leadership; collaborates with global manufacturing, R&D, quality, IT, digital, and site subject-matter experts
* Role responsibilities and qualifications synthesized based on industry benchmark standards.
QUALIFICATIONS & REQUIREMENTS
REQUIRED QUALIFICATIONS
- Master’s or Ph.D. in Data Science, Statistics, Engineering, Life Sciences, or related field
- 5–18 years of experience in data science, analytics, or digital deployment within pharmaceutical or life sciences environments
- Strong statistical modeling, machine learning, coding, and predictive analytics capability using Python, R, SIMCA, or JMP
- Experience with pharmaceutical manufacturing, R&D, GMP operations, TSMS, or process development
- Knowledge of data integration, data quality, data integrity, regulatory compliance, and analytics solution delivery
PREFERRED QUALIFICATIONS
- •Experience with Azure or AWS cloud analytics
- •Familiarity with data pipelines and APIs
- •NLP experience involving unstructured manufacturing knowledge
- •Experience with Power BI, Tableau, Seeq, or Smartsheet
- •Strong global stakeholder management and digital transformation experience
REQUIRED VERIFIED SKILLS
Python
R
SIMCA
JMP
statistical modeling
machine learning
predictive analytics
multivariate analysis
PCA
PLS
process monitoring
anomaly detection
data integration
data quality
GMP
data integrity
regulatory compliance
Power BI
Tableau
Seeq
COMPENSATION & REWARDS
Salary: Competitive / Disclosed upon candidate shortlisting
Benefits: Health and employee benefits, paid leave, retirement benefits, professional development and other company-standard benefits
No salary range is disclosed in the provided job posting. Compensation should therefore be confirmed directly through Lilly's recruitment process rather than estimated from the role title or experience requirement.
ORGANIZATION CONTEXT & CULTURE
Eli Lilly and Company is a global pharmaceutical company focused on discovering and delivering medicines for significant health needs. Lilly operates worldwide and is investing in a Manufacturing and Quality technical hub in Hyderabad to support pharmaceutical manufacturing and quality capabilities.
TEAM SIZE: 50,000+ employees
INDUSTRY: Pharmaceuticals and Biotechnology
Culture: Patient-focused, innovation-driven, collaborative, and science-led culture emphasizing excellence, integrity, respect, and meaningful improvements in health outcomes.
EXPECTED CAREER ROADMAP
The role can progress toward senior data science, advanced analytics, digital manufacturing, technical data science leadership, or broader manufacturing analytics and digital transformation positions within pharmaceutical operations.
APPLICATION ADVISORY
Emphasize pharmaceutical manufacturing or GMP experience; demonstrate practical examples of predictive modeling and multivariate analytics; highlight Python/R, PCA/PLS, process monitoring, and visualization experience; show experience integrating MES/LIMS/ERP or similar scientific and manufacturing data; explain how your analytics work improved quality, process performance, compliance, or operational efficiency; highlight cross-functional and global stakeholder communication.
RECOMMENDED TRAINING
1/5
READY TO SUBMIT?
Verify your capability profile and matching credentials before submitting direct applications.