Senior Research Scientist: Insilico Prediction Platform Lead

** At Elanco (NYSE: ELAN) – it all starts with animals!
**** At Elanco, we pride ourselves on fostering a diverse and inclusive work environment. We believe that diversity is the driving force behind innovation, creativity, and overall business success. Here, you’ll be part of a company that values and champions new ways of thinking, work with dynamic individuals, and acquire new skills and experiences that will propel your career to new heights.
**** Making animals’ lives better makes life better – join our team today!
**** Your Role:
In Silico Structural & Property Prediction Platform Leader
** As the In Silico Structural & Property Prediction Platform Leader, you will drive the strategy, development, and integration of automation, AI, and ML–powered prediction models that accelerate early-stage drug discovery across Elanco’s research portfolio. You will shape the platform vision, partner closely with scientific and technical teams, and enable computational approaches that support both small and large molecule innovation. This position plays a central role in building scalable, data-driven, and automated research capabilities within pharmaceutical R&D.
** Your Responsibilities:*
* • Develop and execute the technical strategy for Elanco’s structural and property prediction platform in alignment with key scientific and therapeutic priorities.  
• Evaluate, select, and implement advanced AI/ML models—including generative, diffusion-based, deep learning, and graph-based approaches—to support small and large molecule discovery.  
• Lead the integration of new computational and automation capabilities into existing discovery workflows and research pipelines.  
• Establish standards and best practices for model ingestion, benchmarking, validation, deployment, reproducibility, and scientific data integrity.  
• Build scalable workflows and automated processes that streamline predictive modeling and improve scientific throughput.  
• Continuously evolve the platform by incorporating stakeholder feedback, monitoring performance indicators, and tracking scientific and technological advancements.
** What You Need to Succeed (minimum qualifications):**•
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* Education:

** Bachelor’s, Master’s, or PhD in molecular biology, biotechnology, bioengineering, bioinformatics, cheminformatics, computational biology, data science, or a related scientific discipline.  *(Scientific domain-first backgrounds are preferred; technical candidates without strong scientific grounding will not be prioritized.)*•
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* Experience:

** 8+ years in computational drug discovery, including at least 5 years leading AI/ML or automation-focused projects or platforms within pharmaceutical or biotech R&D.
• Demonstrated success developing, applying, and deploying advanced computational and automated workflows that accelerate drug discovery, with meaningful impact in large molecule programs.
• Ability to translate complex computational concepts into clear, actionable insights for multidisciplinary scientific and business partners.
** What Will Give You a Competitive Edge (preferred qualifications):*
* • Expertise developing, benchmarking, automating, and deploying state-of-the-art AI/ML models, including deep learning, generative models, diffusion models, GNNs, and transformer-based architectures.
• Strong scientific programming experience (Python, R, or C++), including building, optimizing, and product ionizing cheminformatics and bioinformatics workflows using tools such as RDKit, Tensor Flow, PyTorch, Benchling (or similar), Alpha Fold, Protein LLMs, Schrödinger, Chai, and Boltz; experience with Git-based CI/CD and reproducibility frameworks.
• Deep understanding of the drug discovery pipeline, including ADME/Tox, PK/PD modeling, SAR/QSAR, data analysis, protein engineering, molecular modeling, molecular dynamics/simulation, and structure-based design. Experience in animal health is a plus.
• Proven leadership and communication skills with a track record of influencing interdisciplinary scientific and technical teams and presenting complex modeling concepts to diverse audiences.
• Hands-on experience building scalable or cloud-based computational and…