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Generative Ai Pharmaceutical Jobs in Indiana (NOW HIRING)

... a pharmaceutical company, preferably in animal health. * Demonstrated success identifying novel targets and a proven publication record. * Experience with generative AI (e.g., ProteinMPNN) for de ...

Senior Research Scientist

Indianapolis, IN · On-site

$94K - $120K/yr

... a pharmaceutical company, preferably in animal health. * Demonstrated success identifying novel targets and a proven publication record. * Experience with generative AI (e.g., ProteinMPNN) for de ...

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Generative Ai Pharmaceutical information

What is a generative AI pharmaceutical professional?

A Generative AI Pharmaceutical professional is an expert who leverages artificial intelligence, particularly generative models, to accelerate drug discovery, design new molecules, and optimize pharmaceutical research and development processes. They use advanced algorithms and large datasets to predict how potential drugs will behave and identify promising candidates faster than traditional methods. These professionals often work at the intersection of computer science, biology, and chemistry, collaborating with researchers to bring innovative therapies to market more efficiently. Their work can significantly reduce the time and cost associated with developing new medicines.

How does a generative AI pharmaceutical professional typically collaborate with cross-functional teams?

Generative AI professionals in the pharmaceutical industry frequently work alongside researchers, data scientists, clinicians, and regulatory experts to develop innovative solutions for drug discovery and development. Their role often involves translating complex AI models into actionable insights that support scientific and business objectives. Effective communication and teamwork are essential, as they must ensure that AI-generated data aligns with clinical needs and complies with industry regulations. This collaborative environment provides ample opportunities to learn from experts in various fields and contribute to groundbreaking advancements in medicine.

What are the key skills and qualifications needed to thrive as a generative AI pharmaceutical specialist, and why are they important?

To thrive as a Generative AI Pharmaceutical Specialist, you need a strong background in pharmaceutical sciences, data analysis, and machine learning, typically supported by an advanced degree in a related field. Proficiency with AI frameworks (such as TensorFlow or PyTorch), programming languages like Python, and knowledge of drug discovery platforms are essential. Strong problem-solving abilities, interdisciplinary communication, and adaptability are key soft skills for excelling in this evolving field. These competencies are vital for driving innovation, accelerating drug development, and ensuring effective collaboration between AI and pharmaceutical experts.

What is the difference between Generative Ai Pharmaceutical vs Data Scientist in Pharma?

AspectGenerative Ai PharmaceuticalData Scientist in Pharma
Required CredentialsAdvanced degrees in AI, machine learning, or related fields; knowledge of pharmaceutical dataDegree in Data Science, Statistics, or related fields; experience with healthcare data
Work EnvironmentResearch labs, biotech companies, pharmaceutical firms focusing on AI-driven drug discoveryHealthcare and pharmaceutical companies analyzing clinical and operational data
Industry UsageDevelops AI models for drug design, biomarker discovery, and personalized medicineAnalyzes clinical trial data, patient records, and operational datasets

Generative Ai Pharmaceutical specialists focus on creating AI models to innovate drug development, while Data Scientists in Pharma analyze existing healthcare data to inform decisions. Both roles require strong technical skills but differ in their primary focus within the pharmaceutical industry.

How can generative AI be used in pharmaceuticals?

Generative AI in pharmaceutical roles involves designing new drug molecules, predicting their efficacy and safety, and accelerating the discovery process. It leverages machine learning models to analyze biological data, optimize compound structures, and reduce development timelines, often requiring skills in data analysis and familiarity with AI tools like deep learning frameworks.

What is generative AI in the pharmaceutical industry?

Generative AI in the pharmaceutical industry involves using artificial intelligence models to create new molecular structures, predict drug properties, and assist in drug discovery processes. Pharmaceutical professionals working with generative AI often utilize machine learning tools and require knowledge of bioinformatics and data analysis. This technology accelerates research and reduces development costs by generating novel compounds and optimizing drug candidates.

What are popular job titles related to Generative Ai Pharmaceutical jobs in Indiana?

For Generative Ai Pharmaceutical jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Generative Ai Pharmaceutical jobs in Indiana look for?

The top searched job categories for Generative Ai Pharmaceutical jobs in Indiana are:

What cities in Indiana are hiring for Generative Ai Pharmaceutical jobs?

Cities in Indiana with the most Generative Ai Pharmaceutical job openings:

Advisor, Data Scientist - CMC Data Products

Eli Lilly and Company

Indianapolis, IN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 days ago


Eli Lilly and Company rating

8.8

Company rating: 8.8 out of 10

Based on 63 frontline employees who took The Breakroom Quiz

11th of 86 rated pharmaceutical


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:
The Bioproduct Research & Development (BR&D) organization strives to deliver creative medicines to patients 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.
We are seeking an exceptional Data Scientist with deep data expertise 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. In this role, you'll bridge 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:
  • 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). In addition, Lilly offers a comprehensive benefit program to eligible employees, including 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).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly's compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
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About Eli Lilly

Sourced by ZipRecruiter

Eli Lilly, based in Indianapolis, IN, US, is one of the pioneers in the pharmaceutical industry with a rich history dating back to 1876. This global pharmaceutical company focuses on discovering, developing, manufacturing and selling pharmaceutical products in approximately 120 countries. The company's product categories include endocrinology, oncology, cardiovascular, neuroscience, and immunology. Having invested over $9 billion in research and development in the past decade, Eli Lilly is also committed to creating high-quality medicines that meet real needs. As a recipient of several awards and recognitions, Eli Lilly is known for its focus on life-saving research and drug development. Their mission is to make medicines that help people live longer, healthier, and more active lives.

Industry

Pharmaceutical product wholesalers

Company size

10,000+ Employees

Headquarters location

Indianapolis, IN, US

Year founded

1876