YOUR ROLE
The role involves designing, developing, and implementing cutting-edge models and solutions across a range of quantitative and AI disciplines, including machine learning, optimization, neural networks, and agentic AI
- Design, develop, and implement advanced models in machine learning, optimization, neural networks, and AI domains such as computer vision.
- Partner with business stakeholders to understand requirements, define problem statements, and translate them into effective data science solutions.
- Analyze large and complex datasets to uncover trends, generate insights, and support data-driven decision-making using statistical techniques.
- Develop proof-of-concepts, prototypes, and scalable solutions that clearly demonstrate business value.
- Provide thought leadership in data science and AI, promoting best practices and innovative approaches across projects.
- Prepare and review technical design documentation, ensuring clarity, quality, and alignment with architecture standards.
- Contribute to innovation initiatives, including intellectual property development and potential patent submissions.
- Collaborate with global teams on cross-site data science projects, fostering strong teamwork and knowledge sharing.
- Support local technical leadership in Singapore by ensuring effective project execution and timely delivery.
YOUR SKILLS & EXPERIENCES
- Proven experience in developing and deploying machine learning models and AI solutions in a production or business environment.
- Strong knowledge of statistical methods, data analysis, and predictive modeling techniques.
- Proficiency in programming languages such as Python and familiarity with relevant libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience working with large-scale datasets, data processing tools, and cloud platforms is an advantage.
- Hands-on experience with AI domains such as GenAI, optimization, or deep learning is preferred.
- Solid understanding of data engineering concepts, data pipelines, and model deployment practices is a plus.
- Strong problem-solving skills with the ability to translate business needs into technical solutions.
- Excellent communication skills, with the ability to present complex insights clearly to both technical and non-technical stakeholders.
- Ability to work effectively in cross-functional and global teams.
Preferred Qualifications
- Bachelor's, Master's, or PhD in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- Work experience involving machine learning, computer vision, generative AI, data analytics, or predictive modeling in the domain of Product Test Engineering/Semiconductor Manufacturing
- Exposure to cloud platforms, data engineering concepts, databases, or model deployment practices.
- Experience with data visualization tools such as Power BI, Tibco Spotfire, or Python visualization libraries.
- Familiarity with AI domains such as deep learning, computer vision, optimization, or large language models (LLMs).
