Here's What You'll Do: Support a wide variety of analytical, quality control, and manufacturing processes through advanced data analysis and visualization, statistical modeling, and Bayesian experimental design Apply advanced techniques such as constrained optimization, machine learning, and Monte Carlo simulations to solve complex challenges including schedule optimization and batch generation Identify high-impact opportunities by leveraging and applying the latest advances in computer science and operations research, continuously staying at the forefront of the field Partner closely with cross-functional business and product stakeholders to iteratively align on project goals across the full lifecycle-spanning data acquisition, modeling strategy, validation, deployment, and monitoring Collaborate deeply with data scientists, engineers, research scientists, statisticians, and manufacturing teams to drive integrated, scalable solutions Champion and implement data science and software engineering best practices to ensure robustness, reproducibility, and scalability of solutions Communicate complex analytical findings clearly and effectively to both technical and non-technical audiences, internally and externally Explore and integrate emerging Generative AI capabilities to enhance modeling approaches, accelerate experimentation, and unlock new efficiencies across manufacturing and development workflows Here's What You'll Need (Basic Qualifications) Ph. Collaboration: Work with product management, data engineers and IT teams to implement data quality, security, and automated detection pipelines Data Techniques: Strong understanding of statistical analysis, data mining, and feature engineering.