Short DescriptionOracle is seeking for Data Scientist who will be proficient in using query languages such as SQL and its adaptations. Also have good experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies such as Map Reduce, Spark, HBase, etc., and associated schema.
- An advanced degree in Computer Science, Physics, Engineering, Mathematics, or another relevant quantitative field.
- Excellent understanding of the mathematical theory behind algorithms underlying common machine learning techniques for solving classification and regression problems in a supervised setting as well as approaches for unsupervised learning.
- Multi-years postgraduate experience in AI, machine learning, data mining, analytics and/or predictive modelling.
- Real-world practical experience with machine learning algorithms for classification, regression, clustering, reinforcement learning, dimensional reduction with expertise one or more application domains of NLP, image processing, time series analysis.
- A proven track record in developing, innovating, and applying advanced algorithms to address practical problems and in building new analytical products of commercial value.
- Practical experience in feature engineering, feature evaluation, feature selection and automation of such tasks, model interpretation and visualization.
- Robust knowledge and experience with statistical methods, in particular with the estimation of confidence intervals around parameter values and predicted quantities.
- Domain expertise in one or more of online retail, digital marketing, financial services, insurance, health care, manufacturing, consumer goods, telecommunications.
- Proficiency with several yearsâ?? experience in more than one of Python, R, Java, C, C++, Scala, and robust Linux shell scripting.
- Proficiency in using query languages such as SQL and its adaptations.
- Experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies such as Map Reduce, Spark, HBase, etc., and associated schema.
- Experience with application agile and iterative development practices and version control systems.
- It would be fantastic if you also have.
- A PhD degree in a quantitative Science or technical field.
- Post-doctoral academic research experience in AI and Machine Learning
- Demonstrated experience in engaging and influencing business leaders in solution path design.
- Worked with GPUs and have used CUDA programming.
- Experience with one or more of the DNN frameworks, including TensorFlow, MXNet, Theano, etc. and applications of such libraries to NLP problems.
- Practical experience with deep learning techniques for text processing and modelling.
- Expertise with text processing tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, topic segmentation
- Experience in leading and mentoring other data scientists.