Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse "big data" sources to generate actionable insights and solutions for client services and product enhancement.
Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.
Leading contributor individually and as a team member, providing direction and mentoring to others. Work is non-routine and very complex, involving the application of advanced technical/business skills in area of specialization. 8 years relevant work experience. BS/BA preferred.
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Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.
Within the AI Apps team at Oracle we develop and deploy data science solutions at scale and throughout all of Oracle's existing products and services, and are seeking to grow the team with brilliant and diverse individuals with well-crafted technical ability. This is an exciting and challenging role that will stretch your knowledge and curiosity, offering the opportunity to learn new skills and work within an unusually talented, global community at Oracle.
You will encounter a wide variety of data types, from retail and financial transactions to free text, images and video. AI Apps are required to solve business challenges ranging from recommendation systems and dynamic discounting, management of the flow of goods and services, transportation logistics and movement and storage of materials and inventory, accounting and procurement, project management, manufacturing, staff recruiting, handling and optimizing the HR of an organization
This is a hands-on position where you will be empowered to be creative, ambitious and bold, to solve challenging problems and have the potential to directly impact Oracle's future. The role requires that you have a solid background in machine learning and know how to invent and modify advanced innovative algorithms, applying them to large data sets. You will be a great teammate who is eager to both teach and learn every day, that is enthusiastic and self-motivated to solve useful problems.
More specifically, you will help us solve business and technical problems with robust and statistically sound use of rigorous scientific methodologies and creative use of algorithms using AI, machine (deep, reinforcement) learning and predictive modelling techniques. You should be comfortable in an environment that combines clear problem specifications with sometimes unpredictable situations, carrying unknowns both of technical and functional kind. Given the global setup, you will also be confident and familiar with tools and styles to work remotely in effective ways together with a team located in multiple geographical locations. You will have the opportunity to actively participate as contributor or leader in a team of peer data scientists, understanding the collaborative and transparent relationships with engineering and product teams and the ways of working of an agile environment. When appropriate, we will support and encourage that you strive to publish the best work in the top journals and conferences.
In all, we are looking for ambitious scientists with an uncommon academic background, an ideal blend of coding, machine learning and statistics, a colleague with whom we can share the enjoyment of being curious, the interest in difficult mathematical and algorithmic problems, and the commitment to be innovative in building predictive models as well as in the way society deals with sensitive data.
We would like you to have
* An advanced degree in Computer Science, Physics, Engineering, Mathematics or similar, and postgraduate experience in AI, machine learning, analytics and/or predictive modelling.
* Excellent understanding of the mathematical theory behind common machine learning algorithms for solving classification and regression problems in supervised and unsupervised learning, together with practical experience with the relevant open source libraries.
* Consistency 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, evaluation, 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 industries such as online retail, digital marketing, financial services, insurance, health care, manufacturing, consumer goods, telecommunications.
* Proficiency with several years' experience in more than one of Python, R, Java, C, C , Scala, and robust Linux shell scripting, as well as 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 schemas.
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.
* Experience in a DevOps role or even better in the nascent DataOps role.
* Deep knowledge of graphical models, Bayesian networks, Gaussian processes, MCMC, hidden Markov models and social network analysis.
* Expertise with NLP, text processing and modelling, automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, in particular using deep learning techniques for such tasks, employing popular frameworks, including Keras, TensorFlow, MXNet, Torch, Theano, etc.
* Expertise in Reinforcement Learning and its deep version.
* Experience in leading and mentoring other data scientists.
You will have several opportunities to complete end-to-end execution of the data science process. This will be carried out in a collaborative environment with product and engineering teams, but ranges from understanding business requirements, data discovery and extraction, model development and evaluation, to production pipeline implementation. To do so you will have access to state of the art computational resources, the opportunity to learn by experimenting with technology and the latest open source libraries, a wealth of data to be understood and modelled, and the most friendly and knowledgeable colleagues in a company that offers extraordinary career opportunities for the best.
Join and build the future with us!
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