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  • Emplois similaires à : Senior Data Scientist - CMC Data Products
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Advisor, Data Scientist - CMC Data ProductsBioSpace, Inc. • Indianapolis, Indiana, United States
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Advisor, Data Scientist - CMC Data Products

BioSpace, Inc.
  • US
    Indianapolis, Indiana, United States
  • US
    Indianapolis, Indiana, United States
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À propos

Lilly is a global healthcare leader headquartered in Indianapolis, Indiana, dedicated to discovering and bringing life‑changing medicines to improve patient outcomes worldwide.
Organizational & Position Overview The Bioproduct Research & Development (BR&D) organization delivers creative medicines by developing and commercializing insulins, monoclonal antibodies, novel therapeutic proteins, peptides, oligonucleotide therapies, and gene therapy systems. This multidisciplinary group collaborates closely with discovery and manufacturing teams.
We are seeking an exceptional Data Scientist with deep experience in the pharmaceutical domain to lead the development and delivery of enterprise‑scale data products that power AI‑driven insights, process optimization, and regulatory compliance. The role bridges pharmaceutical sciences with modern data engineering to transform complex CMC, PAT, and analytical data into strategic assets that accelerate drug development and manufacturing excellence.
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
Master’s degree in Computer Science, Data Science, Machine Learning, AI, or related technical field.
8+ years of product management experience focused on data products, data platforms, or scientific data systems and a strong grasp of modern data architecture patterns (data warehouses, data lakes, real‑time streaming).
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 in 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.
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 will also be eligible for a company bonus (depending, in part, on company and individual performance). Lilly offers a comprehensive benefit program to eligible employees, including 401(k) participation, pension, vacation benefits, medical, dental, vision, and prescription drug coverage, flexible benefits (e.g., healthcare and/or dependent day‑care flexible spending accounts), life and death insurance, certain time off and leave of absence benefits, and well‑being benefits such as employee assistance programs, fitness benefits, and employee clubs and activities.
Lilly is dedicated to helping individuals with disabilities actively engage in the workforce, ensuring equal opportunities. If you require accommodation to apply, please complete the accommodation request form for further assistance.
Lilly is a proud 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.
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  • Indianapolis, Indiana, United States

Compétences linguistiques

  • English
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