Oracle-posted 6 months ago
Mid Level
5,001-10,000 employees

The position involves inventing, implementing, and deploying state-of-the-art machine learning and specific domain industry algorithms and systems. The role requires building prototypes and exploring conceptually new solutions while working collaboratively with science, engineering, and product teams to identify customer needs. The goal is to create and implement innovative solutions that drive model implementations and promote innovation. The candidate will apply data science capabilities and research findings to create scalable solutions, developing new intelligence around core products and services through applied research on behalf of customers. Responsibilities include developing models, prototypes, and experiments that pave the way for innovative products and services, as well as building cloud services that work out of the box for enterprises, such as decision support, anomaly detection, forecasting, recommendations, natural language processing (NLP), Natural Language Understanding (NLU), Time Series, Automatic Speech Recognition (ASR), Machine Learning (ML), and Computer Vision (CV). The role also involves designing and running experiments, researching new algorithms, and finding new ways to optimize risk, profitability, and customer experience, while being conversant on ethical problems in consideration of sciences.

  • Invent, implement, and deploy machine learning algorithms and systems.
  • Build prototypes and explore new solutions.
  • Collaborate with science, engineering, and product teams to identify customer needs.
  • Create and implement scalable solutions based on data science capabilities.
  • Develop new intelligence around core products and services through applied research.
  • Develop models, prototypes, and experiments for innovative products and services.
  • Build cloud services for enterprises, including decision support and anomaly detection.
  • Design and run experiments and research new algorithms.
  • Optimize risk, profitability, and customer experience.
  • Strong background in machine learning and data science.
  • Experience with cloud services and enterprise solutions.
  • Proficiency in natural language processing (NLP) and natural language understanding (NLU).
  • Knowledge of time series analysis, automatic speech recognition (ASR), and computer vision (CV).
  • Ability to design and run experiments and research new algorithms.
  • Understanding of ethical considerations in data science.
  • Experience in applied research and developing innovative products.
  • Familiarity with decision support systems and forecasting techniques.
  • Knowledge of customer experience optimization strategies.
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