Advisor, Data Scientist - CMC Data Products

Eli Lilly and Company; India; On-site; INR 11,909,000 - 23,081,000; Full time

Benefits offered by this job

Annual bonus

401(k) plan

Health, dental, and vision coverage

Paid time off

Job summary

Lilly seeks a data product leader to define roadmaps and deliver AI-ready data products across CMC workflows, partnering with discovery, development, and manufacturing. You will design data archetypes, implement compliant data frameworks, and support AI/ML applications for knowledge management and regulatory Q&A.

Cross-functional leadership will be essential as you align data products with quality, regulatory, and analytics goals, enabling self-service access while preserving GxP compliance.

Qualifications

• PhD or MS with pharma data science experience.
• Knowledge of modern data stack technologies and cloud platforms.
• Proficiency with SQL, Python, and data visualization.
• Experience designing data products for AI/ML workflows.

Responsibilities

• Define the roadmap for data products enabling AI/ML applications.
• Define data archetypes and reusable data models aligned with standards.
• Implement data frameworks ensuring 21 CFR Part 11 and ALCOA+ compliance.
• Build training datasets for lab automation and predictive CQA models.
• Collaborate with R&D, process development, manufacturing science, quality, and regulatory affairs.

Skills

SQL

Python

Data visualization

Education

PhD in Computer Science

MS in Computer Science

Tools

Microsoft Fabric

Databricks

Airflow

AWS

Azure

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.

Organizational & Position Overview:

TheBioproductResearch&Development(BR&D)organizationstrivestodelivercreative medicines topatients by developing and commercializing insulins, monoclonal antibodies, novel therapeutic proteins, peptides, oligonucleotide therapies, and gene therapy systems. This multidisciplinary group works collaboratively with our discovery and manufacturing colleagues.

Responsibilities:

Data Product Development: Define the roadmap and deliver analysis‑ready and AI‑ready data products that enable AI/ML applications, PAT systems, near‑time analytical testing, and process intelligence across CMC workflows.

Data Archetypes & Modern Data Management: Define pharmaceutical‑specific data archetypes (process, analytical, quality, CMC submission) and create reusable data models aligned with industry standards (ISA‑88, ISA‑95, CDISC, eCTD).

Modern Data Management for Regulated Environments: Implement data frameworks that ensure 21 CFR Part 11, ALCOA+, and data integrity compliance, while enabling scientific innovation and self‑service access.

AI/ML‑ready Data Products: Build training datasets for lab automation, process optimization, and predictive CQA models, and support generative AI applications for knowledge management and regulatory Q&A.

Cross‑Functional Leadership: Collaborate with analytical R&D, process development, manufacturing science, quality, and regulatory affairs to standardize data products.

Deliverables include:

• Scalable data integration platform that automates compilation of technical‑review‑ready and submission‑ready data packages with demonstrable quality assurance.
• Unified CMC data repository supporting current process and analytical method development while enabling future AI/ML applications across R&D and manufacturing
• Data flow frameworks that enable self‑service access while maintaining GxP compliance and audit readiness
• Comprehensive documentation, standards, and training programs that democratize data access and accelerate product development

Basic Requirements:

• PhD in Computer Science, Data Science, Machine Learning, Biomedical / Medical Informatics, Computational Biology, AI, or closely related STEM degree and 0-5 years of pharmaceutical industry experience; or
• Master of Science in Computer Science, Data Science, Machine Learning, AI, Computational Biology, Biostatistics / Applied Statistics / Statistics, or closely related STEM degree and 5+ years of pharmaceutical industry experience.
• Knowledge of modern data stack technologies(Microsoft Fabric, Databricks, Airflow) and cloud platforms (AWS- S3, RDS, Lambda/Glue, Azure).
• Demonstrated experience designing data products that support AI/ML workflows and advanced analytics in scientific domains.
• Proficiency with SQL, Python, and data visualization tools.
• Experience with analytical instrumentation and data systems(HPLC/UPLC, spectroscopy, particle characterization, process sensors).
• Knowledge of pharmaceutical manufacturing processes, including batch and continuous manufacturing, unit operations, and process control.
• Expertise with data modeling for time‑series, spectroscopic, chromatographic, and hierarchical batch/lot data.
• Experience with laboratory data management systems (LIMS, ELN, SDMS, CDS) and their integration patterns.

Additional Preferences:

• Understanding of Design of Experiments (DoE), Quality by Design (QbD), and process validation strategies.
• Experience implementing data mesh architectures in scientific organizations.
• Knowledge of MLOps practices and model deployment in validated environments.
• Familiarity with regulatory submissions(eCTD, CTD) and how analytical data supports marketing applications.
• Experience with CI/CD pipelines (GitHub Actions, CloudFormation) for scientific applications.

Lilly 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 is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is

$126,000 - $244,200

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance).

• 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).

We are dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions.

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