BluNova is a subsidiary of Blue Label Telecoms responsible for drawing value from its large heterogeneous corpus of data originating from multiple companies within the Blue Label group. With this data we identify opportunities in the market and develop sustainable solutions to exploit these opportunities. We leverage scalable cloud technologies to deploy our solutions, with a strong emphasis on automation. Most of our data analysis is performed in a distributed spark environment, where we have leg room to spin up large clusters exceeding thousands of cores and terabytes of ram when needed.<\/p>\n
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Job Title: Associate Data Scientist<\/strong> Job Summary:<\/strong> Requirements:<\/strong> Data Gathering:<\/strong> Data Platform:<\/strong> Data Science:<\/strong> Security and Compliance:<\/strong> Data Evangelism and Innovation:<\/strong> Stakeholder Management:<\/strong> Self-Management:<\/strong>
\nLocation:<\/strong> Sandton, Gauteng, South Africa
\nReference #:<\/strong> B079
\nContract Type:<\/strong> Permanent
\nSalary:<\/strong> Market Related<\/p>\n
\nResponsible for discovering insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals.<\/p>\n
\nRESPONSIBILITIES:<\/strong><\/p>\n
\nWork with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
\nMine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
\nAssess the effectiveness and accuracy of new data sources and data gathering techniques.
\nSupport sourcing of new data to develop data flows into the platform and enable sanitation of data
\nUnderstand the breadth of our data sets and engage in interactive data exploration and data-driven story-telling
\nEnsure that informative datasets are appropriately served for analytics and BI applications.<\/p>\n
\nCollaborates with data engineer to scope and build data platform to enable data modelling, exploration and mining at large scale.
\nEnsure that informative datasets are served in the BI layer.<\/p>\n
\nInteraction with business units to understand business models and value drivers.
\nOngoing data exploration to identify opportunities, limitations and gaps in the acquired data.
\nPrepare analytical datasets to visualize value drivers against various metrics.
\nBuild machine learning \/ predictive models on analytical datasets to uplift value drivers.
\nCross-validate predictive models and transparently report on accuracy.
\nDemonstrates the following scientist qualities: collaboration, clarity, accuracy, precision, relevance, depth, breadth, logic, significance, and fairness.
\nProvides on-going tracking and monitoring of performance of decision systems and statistical models.
\nContinuously improves methods and algorithms.
\nWorks transparently, ensures that all analysis is reproducible and uses version control appropriately for collaboration.<\/p>\n
\nWorks with the ISO to ensure that the information used is in compliance with the regulatory and security policies in place.
\nQualifies where information can be stored or what information, external to the organization, may be used in support of the use case.
\nCollaborates with the ISO to ensure that the information used follows the compliance, access management, and control policies and that it meets the qualification and assurance requirements of the Group<\/p>\n
\nKnowledge sharing
\nApplication brainstorming
\nAvailability as a big data subject matter expert to the Blue Label Group
\nPromote data driven business approach.
\nParticipation in big data communities \/ open source<\/p>\n
\nPresents and depicts the rationale of their findings in easy to understand terms for the business.
\nCommunicates and works with business subject matter experts.
\nEducates the organization both from IT and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results.
\nHelps the organization understand the principles and the math behind the process to drive organizational buy-in and manage expectations<\/p>\n
\nFollow through to ensure that personal quality and productivity standards are consistently and accurately maintained
\nDemonstrate consistent application of internal procedures
\nPlan and prioritise, demonstrating abilities to manage competing demands
\nDemonstrate abilities to anticipate and manage change
\nDemonstrate flexibility in balancing achievement of own objectives with abilities to understand and respond to organizational needs<\/p>\n