Data Scientist 4

Design, Development and implementation of advanced machine learning algorithms as well as physics-based software solutions for our hybrid metrology systems including optical metrology solutions. Design and development of sophisticated algorithms for image segmentation and classification specific to our metrology systems Provide strategic direction for the integration of advanced analytics, machine learning, and AI technologies. Select and evaluate data science tools, frameworks, and platforms to build a cohesive and efficient data science ecosystem. Hands On ML Model development and derive the right solutions for complex problems. Rapid prototyping and validation of new machine learning as well as deep learning algorithms. Work closely with software, system engineering and data-science teams to integrate algorithms into product systems as well as contributing to cross-functional innovations. Work with internal and external customer and stakeholders to define the requirements for next generation ML algorithm requirements to solve challenging customer problems Datascience related escalation management and troubleshooting potential issues from the field systems Prepare presentations to all stakeholders and be able to host design reviews Collaborate effectively with global development teams to ensure seamless deployment and continuous improvement. Stay abreast of emerging technologies to ensure the continuous evolution of our data science capabilities. Extensive experience with data analytics, supervised and unsupervised machine learning including regression models, decision trees, feature engineering, frameworks like Pytorch, TensorFlow, SciKit-learn etc. Familiarity with MLOps with Databricks is a strong advantage. Strong background in optical physics, numerical simulations, advanced signal processing, computer vision and spectroscopy. Experience working with and handling huge datasets from advanced sensors and imaging systems. Proficiency in programming languages (e.g., Python, R) and familiarity with data science libraries and frameworks. Familiarity with C# is an added advantage Ability to analyze large datasets and validate models for accuracy, robustness and reliability. Experience with ML deployment and monitoring strategies to track model performance over time and address issues proactively. Ability to work cross‑functionally and communicate complex modelling concepts to mixed engineering audiences. Curiosity-driven and a structured problem-solver Background in parallel/distributed computing, profiling and optimization for computation and memory Experience working in the development of semiconductor capital equipment systems is preferable. PhD or MSc in Physics, Applied Physics, Electrical Engineering, Optical Engineering or related field with strong modelling/analytical background. a minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience