Primary Responsibility, but not limited to
- Designs, develops, and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement.
- Interacts with product and service teams to identify questions and issues for data analysis and experiments.
- Develops and codes software programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
- Deploys data science models and lead the end-to-end life cycle, including solution design, development, deployment, model maintenance and monitoring.
- Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.
Requirements
- Experience and deep understanding of advanced analytics and modern machine learning techniques.
- Hands-on experience with image and video analysis techniques and frameworks, such as traditional computer vision, object detection, image classification etc.
- Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques.
- Experience with data visualization tools (Tableau, PowerBI etc) and techniques, able to use visual tools to communicate data findings to non-technical audience.
- Strong software development skills.
- Fluency in Python.
- Strong verbal and written communication skills.
Good to have:
- Exposure to the semiconductor industry.
- Exposure to image processing systems hardware.
- Experience working with cloud services e.g GCP, AWS and/or Cloud certifications.
- Experience working with software engineering best practices (version control, agile, devops), especially MLOps.
- Experience in other languages (Rust, R, C++ etc).
- Experience in web development (Angular, React etc).
