Applied Scientist 4

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),  Text-To-Speech (TTS), 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.

Career Level - IC4

Defines the bar for science practices, and helps teams achieve those goals.  Develop deep product intuition to influence future product roadmaps and drive decision making. Clearly articulate technical work to audiences of all levels and across multiple functional areas in both internal and external settings. Engage in forward looking research with a global team. Identifies and mitigates risks across full set of systems, particularly at the intersection of business and engineering. 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. Hires and mentors across the org. Perform an active role in team planning, review and retrospective events. Ensures experiments are ready for hand-off to Software Developers ship into production.

• Is very experienced with Machine Learning and Deep Learning models and frameworks
• Has background on speech processing (speech recognition, speaker 
  verification/identification, keyword spotting, diarization, TTS) and/or neural language 
  modeling and/or big data management and curation
• Has strong programming skills in Python. C++, Java are beneficial, but not required.
• Has 6+ years of professional development
• Is able to experiment and evaluate state of the art systems from both academia and 
  industry
• Possesses excellent communication skills with an ability to explain and write 
  specifications that embody complex concepts to stakeholders within the team
• Is able to adapt to a fast-paced work environment and can quickly adjust to changing 
  priorities
• Works in a detail-oriented manner, with a focus on quality of the product, data, and 
  code
• Is fluent in spoken/read/written English.
  An exposure to medical/health use cases is a plus.
  A PhD in computer science on natural language processing or speech processing is 
  preferred but not a must.
  A relevant publication record is a plus.

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