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Data Scientist
2 months ago
At Oracle, we are seeking an exceptional Applied Scientist to join our team. As an Applied Scientist, you will be responsible for inventing, implementing, and deploying state-of-the-art machine learning and/or specific domain industry algorithms and systems.
Key Responsibilities:
- Apply data science capabilities and research findings to create and implement solutions to scale.
- Develop new intelligence around core products and services through applied research on behalf of our customers.
- Design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
- 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).
- Conversant on ethical problems in consideration of sciences.
- Identify data science use cases and design scalable solutions that can be built as a feature of the product/service.
- Contributes to writing production model code.
- Work with Software Engineering teams to deploy them in production.
- Set up environment needed to run experiments for all projects.
- Set up distributed environments.
- Design and implement algorithms, train models, and deploy both to production to validate premises and achieve goals.
- Design and execute offline/online experiments and model performance testing.
- Work with large, complex data sets.
- Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed.
- Address business/customer problems and questions using statistical and machine learning techniques to achieve business goals and KPI's.
- Come up with innovative solutions to address tradeoffs or challenges faced by team.
- Stay up-to date with research and trends regarding latest algorithms in ML or other industry/domain space.
- Perform research in emerging areas, which may include efficient neural network development including quantization, pruning, compression and neural architecture search, as well as novel differentiable compute primitives.
Requirements:
- Strong background in machine learning, data science, and software engineering.
- Experience with cloud services, natural language processing, and computer vision.
- Excellent problem-solving skills and ability to work in a fast-paced environment.
- Strong communication and collaboration skills.
- Ability to design and implement algorithms, train models, and deploy them to production.
- Experience with large, complex data sets and ability to solve difficult, non-routine analysis problems.
