Preferred QualificationsPrincipal Data Scientist – HyderabadOracle Applications Labs (OAL) runs Oracle software that runs Oracle. OAL is responsible for implementing, running, and improving nearly all of Oracle's Enterprise On-Premise and Cloud Applications. We use Oracle’s business requirements as a "test bed" for innovation. We often are ahead of the standard product road map and build extensions and custom applications to meet the needs of our 120,000-employee, Fortune 100 Company. Once proven, our ideas and innovations quickly find their way back into the core product. We also ensure that Oracle is always Oracle’s best reference for our enterprise applications and analytics solutions and platforms. We are seeking to grow the data science capabilities with brilliant and diverse individuals with exceptional technical ability. This is a challenging role that will stretch your knowledge and curiosity, while at the same time is a great opportunity to learn new skills and work within an unusually talented, global community at OracleAs a Principal Data Scientist, you will be responsible for driving the top-level data science strategy for OAL. You will be the go-to person and provide guidance to enable Machine Leaning and AI development and be a hands-on person inventing advanced innovative algorithms, and to solve challenging business problems. The role requires that you have an extensive background in machine learning and data mining. You will be defining reference architecture, ML/AI life-cycle, technical platform and development processes that helps other OAL teams to deploy ML/AI capabilities for their application and analytical solutions. You will be a team player who is eager to both teach and learn daily, that is proactive and self-motivated and has excellent communication skills. Key Responsibilities:•Define and document the full life-cycle of data science products development from data collection, aggregation, feature engineering, visualization, productionization, and monitoring •Complete end-to-end execution of the data science processes experimentation and documentation•Solve business and technical problems with robust and statistically sound use of rigorous scientific methodologies and creative use of algorithms using AI, machine/deep learning and predictive modelling techniques•Make consistent use of solid verbal, interpersonal and written communication skills to carefully document findings and share results with various stakeholders•Work effectively with global teams located in multiple geographical locations•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•Work effectively with global teams located in multiple geographical locations•Able to present complex analysis results to both technical and non-technical audiences.Qualification:•An advanced degree in Computer Science, Statistics, Engineering, Mathematics, or another relevant quantitative field•7+ years of proven track record of data mining and data science•Practical experience with machine learning algorithms for classification, regression, clustering, recommender systems, reinforcement learning, dimensionality reduction •A proven track record in developing, innovating, and applying advanced algorithms to address practical problems and in building new predictive analytic products•Practical experience in feature engineering, feature evaluation, feature selection and automation of such tasks, model interpretation and visualization•Domain expertise in one or more of Software, technical or digital marketing, manufacturing•Proficiency with several years’ experience in more than one of Python, PySpark, R, Java, C++, Scala, and Spark•Experience with big data processing engines like Spark, Kafka is a plus•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 schemas•Working experience in data warehousing, data integration, and visualization •Experience with application of Agile and iterative development practices and DevOps processes•Lead, Influence, and guide other data scientists•Team player with great communication and presentation skills.
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