Applied Scientist

Invent, implement and deploy state-of-the-art machine learning and/or specific domain industry algorithms and systems. Build prototypes and explore conceptually new solutions. Work collaboratively with science, engineering, and product teams to identify customer needs in order to create and implement solutions, promote innovation and drive model implementations. Applies data science capabilities and research findings to create and implement solutions to scale. Responsible for developing new intelligence around core products and services through applied research on behalf of our customers. Develops models, prototypes, and experiments that pave the way for innovative products and services. Build cloud services that work out of the box for enterprises, e.g. decision support, anomaly detection, forecasting and recommendations), natural language processing (NLP), Natural Language Understanding (NLU),Time Series, Automatic Speech Recognition (ASR), Machine Learning (ML), and Computer Vision (CV). Design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. Conversant on ethical problems in consideration of sciences.

Leading contributor providing guidance and mentorship to define, design and deliver product quality improvements from ideation stage to shipping to the customer. Write high quality code to power experiments and build models. Contributes to writing production model code. Work closely with product management and engineering to deliver products which solves the needs of our customers by building relevant, innovative results which strategically differentiates Oracle in the market. Set up environment needed to run experiments for all projects. Set up distributed environments. Engage with customers and help solve complex problems with the customer/partner. Directly impact our customers via innovation in products and services that make use of ML/AI technology. Clearly articulate technical work to audiences of all levels and across multiple functional areas. Keep track of the progress and ensure the team is following the best practices. Works on training data collection, feature engineering, model training, offline and online experimentation. Drives independent research and development. Advance the state-of-the-art machine learning and algorithms for real-world large-scale applications. Ensure solutions are designed with fairness and explainability in mind. May perform other duties as assigned.