Data Scientist 3

Design, develop, and deploy scalable AI/ML and Generative AI solutions including production-ready models on cloud platforms (preferably Azure) using strong MLOps practices.

Build and evaluate machine learning architectures for scientific and engineering applications such as Scientific Machine Learning, surrogate modeling, digital twins, and simulation-driven AI.

Lead technical design discussions, foster innovation, partner with cross-functional teams, and establish governance and monitoring for model reliability.

5+ years of experience delivering enterprise-scale data science and AI/ML solutions.

Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Engineering, Applied Mathematics, Physics, or related field.

Strong programming skills in Python or R, hands-on experience with PyTorch and modern deep learning techniques.

Experience with cloud platforms (Azure, AWS, or GCP), big-data technologies, MLOps, model deployment, and machine learning applied to scientific computing or engineering simulations.

Experienced leader capable of guiding complex AI/ML projects and teams in high-impact technical environments using agile methodologies.

Strong domain knowledge in scientific computing, engineering simulations, and advanced AI techniques like Physics-Informed AI, Neural Operators, and Digital Twin technologies.

Operates well in collaborative, cross-disciplinary roles translating business problems into technical solutions with measurable impact.