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A giant in the telecommunications industry is looking for a Intermediate Data Scientist to join their dynamic team based in Johannesburg to apply operations research and statistical methods to solve challenges related to Cloud compute, storage, network, and capacity for public cloud analytics and ML/AI platforms. You will work broadly across the Analytics and Big Data Platforms, Platforms Engineering and Systems Infrastructure teams to optimize the deployment of resources and drive innovation in the analytics and big data public cloud software stack, allowing for efficient use of resources. Key accountabilities and decision ownership:Lead projects with hands-on analysis and modelling, drawing from multiple of analytical methods to choose the right tool and right level of complexity appropriate for the cloud based technology challenges.Engage broadly with the organization to identify, prioritize, frame, and structure complex and ambiguous challenges, where advanced analytics projects or tools can have the biggest impact.Identify, communicate and resolve the cloud based platform operational challenges and leverage public cloud analytical & ML/AI capabilities.Articulate operational problem statements and questions and use mathematical techniques to arrive at an answer using data. Translate analysis results into data driven recommendations.Collect, analyse, and interpret large data sets using analytical, statistical, and programming skills.Discover information, patterns in huge amount of data and build models with the purpose of automating activities within the process to support various use cases.Apply machine learning algorithms to harness public cloud big data power and leverage the capabilities of emerging cloud based technology.Write code using Python, R, Scala, Java and SQL in order to build analytics modules using big data architectures.Build prototypes to support use cases and showcase them to business in order to obtain their buy in.Transition prototypes into production grade use cases by applying Well-Architected framework and principles.Periodically, review production models and optimise or decommission where required.Research, investigate and evaluate new technologies and methods to improve advance analytics and machine learning capabilities. Core competencies, knowledge and experience:Statistical analysis: Identify patterns in data. This includes having a keen sense of pattern detection and anomaly detection.Machine learning: Implement algorithms and statistical models to enable a computer to automatically learn from data.Computer science: Apply the principles of artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering.Programming: Write computer programs and analyze large datasets to uncover answers to complex problems.Data storytelling: Communicate actionable insights using data.Analytical thinking. Find analytical solutions to abstract business issues.Critical thinking: Apply
https://protool.gumtree.co.za/external-link-browser.html?url=aHR0cHM6Ly9lbi16YS53aGF0am9icy5jb20vY29vcG9iX19jcGxfX18xMjY2XzQ3Mjg5X180OTc/dXRtX3NvdXJjZT1ndW10cmVlJnV0bV9tZWRpdW09ZmVlZCZrZXl3b3JkPQ==&jid=1177962&xid=1266_47289
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