October 29, 2021
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Johannesburg, Gauteng, South Africa
October 29, 2021
Apply NowJob description
Responsibilities will include:
 Develop and implement a reusable architecture of data pipelines to make data available for various purposes including Machine Learning (ML), Analytics and Reporting
 Work collaboratively as part of team engaging with system architects, data scientists and business in a healthcare context
 Define hardware, tools and software to enable the reusable framework for data sharing and ML model productionization
 Work comfortably with structured and unstructured data in a variety of different programming languages such as SQL, R, python, Java etc
 Understanding of distributing programming and advising data scientists on how to optimally structure program code for maximum efficiency
 Build data solutions that leverage controls to ensure privacy, security, compliance and data quality
 Understand meta-data management systems and orchestration architecture in the designing of ML/AI pipelines
 Deep understanding of cutting edge cloud technology and frameworks to enable Data Science
 System integration skills between Business Intelligence and source transactional
 Improving overall production landscape as required
 Define strategies with Data Scientists to monitor models post production
 Write unit tests and participate in code reviews
Technical skills core:
 Expert in programming languages such as R, Python, Scala and Java
 Expert database knowledge in SQL and experience with MS Azure tools such as Data Factory, Synapse Analytics, Data Lake, Databricks, Azure stream analytics and PowerBI
 Modern Azure datawarehouse skills
 Expert Unix/Linux admin experience including shell script development
 Exposure to AI or model development
 Experience working on large and complex datasets
 Understanding and application of Big Data and distributed computing principles (Hadoop and MapReduce)
 ML model optimization skills in a production environment
 Production environment machine learning and AI
 DevOps/DataOps and CI/CD experience
Technical skills additional:
 AWS experience
Professional Qualifications & Experience
 Honours or Masters degree in BSc Computer Science
 Honours or Masters degree in Engineering or Software Engineering with solid experience in data mining and machine learning
 Other qualifications will also be considered if accompanied by the relevant experience
 5 to 15 years of experience is preferred
 Develop and implement a reusable architecture of data pipelines to make data available for various purposes including Machine Learning (ML), Analytics and Reporting
 Work collaboratively as part of team engaging with system architects, data scientists and business in a healthcare context
 Define hardware, tools and software to enable the reusable framework for data sharing and ML model productionization
 Work comfortably with structured and unstructured data in a variety of different programming languages such as SQL, R, python, Java etc
 Understanding of distributing programming and advising data scientists on how to optimally structure program code for maximum efficiency
 Build data solutions that leverage controls to ensure privacy, security, compliance and data quality
 Understand meta-data management systems and orchestration architecture in the designing of ML/AI pipelines
 Deep understanding of cutting edge cloud technology and frameworks to enable Data Science
 System integration skills between Business Intelligence and source transactional
 Improving overall production landscape as required
 Define strategies with Data Scientists to monitor models post production
 Write unit tests and participate in code reviews
Technical skills core:
 Expert in programming languages such as R, Python, Scala and Java
 Expert database knowledge in SQL and experience with MS Azure tools such as Data Factory, Synapse Analytics, Data Lake, Databricks, Azure stream analytics and PowerBI
 Modern Azure datawarehouse skills
 Expert Unix/Linux admin experience including shell script development
 Exposure to AI or model development
 Experience working on large and complex datasets
 Understanding and application of Big Data and distributed computing principles (Hadoop and MapReduce)
 ML model optimization skills in a production environment
 Production environment machine learning and AI
 DevOps/DataOps and CI/CD experience
Technical skills additional:
 AWS experience
Professional Qualifications & Experience
 Honours or Masters degree in BSc Computer Science
 Honours or Masters degree in Engineering or Software Engineering with solid experience in data mining and machine learning
 Other qualifications will also be considered if accompanied by the relevant experience
 5 to 15 years of experience is preferred
