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Advisor R&D

Job in Indianapolis, Hamilton County, Indiana, 46262, USA
Listing for: Elanco
Full Time position
Listed on 2026-08-22
Job specializations:
  • Research/Development
    Data Scientist
Salary/Wage Range or Industry Benchmark: 150000 - 210000 USD Yearly USD 150000.00 210000.00 YEAR
Job Description & How to Apply Below
Location: Indianapolis

At Elanco (NYSE: ELAN) – it all starts with animals!


As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets.
At Elanco, we are driven by our vision of Food and Companionship Enriching Life and our purpose – all to Go Beyond for Animals, Customers, Society and Our People.


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!


Senior Machine Learning & Computer Vision Scientist – R&D

Your Role:

As the Senior Machine Learning & Computer Vision Scientist, you will accelerate Elanco’s R&D portfolio by turning proprietary scientific data into predictive models that guide drug discovery and development decisions. You will partner with discovery and development scientists to build machine learning and computer‑vision models on molecular, in vitro, ADMET, and imaging data to support target identification, molecular optimization, digital biomarkers, and endpoint prediction for animal health.

Your Responsibilities:

  • Lead ML/CV work for key R&D programs, partnering with scientists to turn target identification, molecular optimization, in vitro analysis, ADMET, and biomarker questions into modeling problems with clear success criteria.
  • Design, build, and validate advanced ML and computer‑vision models—including CNNs, transformers, graph neural networks, and generative approaches—on multi‑modal data (molecular, assay, imaging, behavioral) to deliver reliable predictions and classifications.
  • Shape data collection, annotation, and synthetic data usage by working with experimental teams on capture protocols, labeling standards, and quality checks; evaluate synthetic data and augmentation to strengthen sparse datasets while managing bias and risk.
  • Operationalize models in R&D workflows by integrating them with tools used by scientists—including building and deploying models in Databricks—and influencing standards for reproducibility, documentation, monitoring, and model governance.
  • Provide technical leadership and mentorship by guiding junior scientists, leading cross‑functional modeling initiatives, and clearly communicating technical concepts and results to diverse stakeholders.
What You Need to Succeed (minimum qualifications):
  • Education & baseline experience:
    PhD in a quantitative field (e.g., Data Science, Engineering, Physics, Mathematics, Statistics, Bioinformatics, Computational Chemistry), or a Master’s degree with substantial hands‑on ML/CV experience.
  • Applied ML/CV experience: 7+ years of industry experience building and deploying ML and computer‑vision models for scientific problems in biomedical, pharmaceutical, or related domains, with demonstrated impact and close collaboration with wet‑lab or clinical teams.
  • Technical and collaboration skills:
    Strong Python skills and proficiency with modern ML/CV libraries (e.g., PyTorch, Tensor Flow, scikit‑learn, OpenCV), solid understanding of statistics and experimental design, and proven ability to work and communicate effectively in cross‑functional, matrixed environments.
What will give you a competitive edge (preferred qualifications):
  • Domain expertise and impact:
    Experience in animal health, pharmaceutical, or biotech R&D, with a record of impactful ML/CV applications (e.g., chemo informatics, bioinformatics, digital biomarkers) shown through projects, publications, or patents.
  • Advanced technical depth and platforms:
    Hands‑on expertise with methods such as neural networks and generative models, plus practical experience operationalizing models using Databricks and MLOps tools in production‑like or scaled environments.
  • Leadership and influence:
    Demonstrated success leading cross‑functional teams, mentoring junior scientists, and influencing scientific and technical…
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